Electrical and Electronics Engineering publications abstract of: 02-2018 sorted by title, page: 12

» Modular Multilevel Converter DC Fault Protection
Abstract:
High-voltage direct current (HVDC) grids will require the development of dc protections that provide fast fault isolation and minimize the disturbance caused to the existing ac power networks. This paper investigates how the dc fault recovery performance of a half-bridge modular multilevel converter (HB-MMC) is impacted by different dc protection design choices. An HB-MMC point-to-point HVDC system that is protected with dc circuit breakers (CBs) is simulated on a real-time digital simulator using detailed switch models of the converters and switch gear. A dc CB controller has been developed and implemented in a software-in-the-loop fashion, and has been made available free for download. A novel blocking scheme for the HB-MMC is proposed, which limits the prospective dc-side fault current, benefiting dc switch gear. A comparison of circulating current controllers shows that the standard dq controller is likely to be unsuitable for fault studies. Finally, benchmarking shows that a 48% reduction in power-flow recovery time and a 90% reduction in the energy dissipated in the circuit breaker can be achieved, along with other benefits, depending on the protection design.
Autors: O. Cwikowski;H. R. Wickramasinghe;G. Konstantinou;J. Pou;M. Barnes;R. Shuttleworth;
Appeared in: IEEE Transactions on Power Delivery
Publication date: Feb 2018, volume: 33, issue:1, pages: 291 - 300
Publisher: IEEE
 
» Moisture Prevention in a Pre-Purged Front-Opening Unified Pod (FOUP) During Door Opening in a Mini-Environment
Abstract:
Contamination in a wafer transportation box [e.g., a front-opening unified pod (FOUP)] can influence device yield and performance. Additional precautions might be required to prevent outside contamination during FOUP door opening. This paper experimentally examines moisture evolution in a pre-purged FOUP with an open door in a mini-environment. Air curtains of different widths () were employed to prevent outside moisture intrusion, and their performance was compared with that of a conventional purge method. Clean dry air was used as the supplied gas in experiments. A moisture prevention index (MPI) was further introduced as a tool for interpreting results. When the conventional purge method was used, moisture in the mini-environment was rapidly transferred into the FOUP, and relative humidity (RH) reached approximately the same levels as the mini-environment, indicating poor moisture prevention performance. RH values were much lower when the air curtain was used. The best moisture prevention performance was observed for a system using an air curtain with mm. The MPIs for the conventional purge method were approximately 8.0%–8.4%, whereas those for the air curtain application ranged from 40%–100%. Most importantly, the MPIs for and 70 mm reached or exceeded 90%.
Autors: Tee Lin;Ben-Ran Fu;Shih-Cheng Hu;Yi-Han Tang;
Appeared in: IEEE Transactions on Semiconductor Manufacturing
Publication date: Feb 2018, volume: 31, issue:1, pages: 108 - 115
Publisher: IEEE
 
» Monolithic Red/Green/Blue Micro-LEDs With HBR and DBR Structures
Abstract:
In this letter, monolithic red, green, and blue (RGB) micro light-emitting diodes (LEDs) were fabricated using gallium nitride based blue micro LEDs and quantum dots (QDs). Red and green QDs were sprayed onto individual region surrounded by patterned black matrix photoresist on the blue micro LEDs to form color conversion layers. Owing to its light-blocking capability, the patterned black matrix photoresist improved the contrast ratio of the micro LEDs from 11 to 22. To enhance the color conversion efficiency and the light output intensity, a hybrid Bragg reflector (HBR) was deposited on the bottom side of the monolithic RGB micro LEDs, thus reflecting the RGB light emitted to the substrate. To further improve the color purity of the red and green light, a distributed Bragg reflector (DBR) with high reflection for the blue light was deposited on the top side of the QDs/micro LEDs. The red and green light output intensities of the micro LEDs with HBR and DBR were enhanced by about 27%.
Autors: Guan-Syun Chen;Bo-Yu Wei;Ching-Ting Lee;Hsin-Ying Lee;
Appeared in: IEEE Photonics Technology Letters
Publication date: Feb 2018, volume: 30, issue:3, pages: 262 - 265
Publisher: IEEE
 
» More documentaries for engineers [Resources Reviews]
Abstract:
Last August, IEEE Spectrum plucked three films from the video deluge that we felt were particularly suited for engineers. Now, we've waded back in to bring you three more apropos documentaries that have recently become available to stream or download.
Autors: Stephen Cass;
Appeared in: IEEE Spectrum
Publication date: Feb 2018, volume: 55, issue:2, pages: 22 - 22
Publisher: IEEE
 
» MoTe2: A Promising Candidate for SF6 Decomposition Gas Sensors With High Sensitivity and Selectivity
Abstract:
In this letter, we took a first principles calculation of five SF6 decomposition gas molecules (SO2, H2 S, SOF2, SO2F2, and SF6) adsorption on monolayer MoTe2. By calculating adsorption energy, charge transfer, and work function combined with differential charge density analysis, we predict that MoTe2 is sensitive and selective to the SO2 molecule. Furthermore, the total density of states analysis and projected density of states analysis demonstrate that the orbital hybridization is the main reason of the intense charge transfer between the SO2 molecule and monolayer MoTe2. In summary, it can be concluded that MoTe2 is a promising candidate for SF6 decomposition gas sensors with high sensitivity and selectivity.
Autors: Da-Wei Wang;Xiao-Hua Wang;Ai-Jun Yang;Ji-Feng Chu;Pin-Lei Lv;Yang Liu;Ming-Zhe Rong;
Appeared in: IEEE Electron Device Letters
Publication date: Feb 2018, volume: 39, issue:2, pages: 292 - 295
Publisher: IEEE
 
» Motion-Based Rapid Serial Visual Presentation for Gaze-Independent Brain-Computer Interfaces
Abstract:
Most event-related potential (ERP)-based brain–computer interface (BCI) spellers primarily use matrix layouts and generally require moderate eye movement for successful operation. The fundamental objective of this paper is to enhance the perceptibility of target characters by introducing motion stimuli to classical rapid serial visual presentation (RSVP) spellers that do not require any eye movement, thereby applying them to paralyzed patients with oculomotor dysfunctions. To test the feasibility of the proposed motion-based RSVP paradigm, we implemented three RSVP spellers: 1) fixed-direction motion (FM-RSVP); 2) random-direction motion (RM-RSVP); and 3) (the conventional) non-motion stimulation (NM-RSVP), and evaluated the effect of the three different stimulation methods on spelling performance. The two motion-based stimulation methods, FM- and RM-RSVP, showed shorter P300 latency and higher P300 amplitudes (i.e., 360.4–379.6 ms; 5.5867–) than the NM-RSVP (i.e., 480.4 ms; ). This led to higher and more stable performances for FM- and RM-RSVP spellers than NM-RSVP speller (i.e., 79.06±6.45% for NM-RSVP, 90.60±2.98% for RM-RSVP, and 92.74±2.55% for FM-RSVP). In particular, the proposed motion-based RSVP paradigm was significantly beneficial for about half of the subjects who might not accurately perceive rapidly presented static stimuli. These results indicate that the use of proposed motion-based RSVP paradigm is more beneficial for target recognition when developing BCI applications for severely paralyzed patients with com- lex ocular dysfunctions.
Autors: Dong-Ok Won;Han-Jeong Hwang;Dong-Min Kim;Klaus-Robert Müller;Seong-Whan Lee;
Appeared in: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Publication date: Feb 2018, volume: 26, issue:2, pages: 334 - 343
Publisher: IEEE
 
» Moving Point Target Detection Based on Higher Order Statistics in Very Low SNR
Abstract:
This letter presents an approach for the detection of moving point targets on high-frame-rate image sequences with low spatial resolution and low SNR based on higher order statistical theory. We propose a novel method for analyzing the time-domain evolution of image data for distinguishing between the background and the target in situations when the spatial signal of the target is swamped by noise. Our method is formulated to detect a time-domain transient signal of unknown scale and arrival time in noisy background. We proposed a bispectrum-based model to characterize the temporal behavior of pixels, and the detection ability under different frame rates and SNRs is analyzed. The method is evaluated using both simulated and real-world data, and we provide a comparison to other widely used point target detection approaches. Our experimental results demonstrate that our algorithm can efficiently detect extremely low SNR targets that are virtually invisible to humans based on time-domain analysis of image sequences.
Autors: Wenlong Niu;Wei Zheng;Zhen Yang;Yong Wu;Balazs Vagvolgyi;Bo Liu;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Feb 2018, volume: 15, issue:2, pages: 217 - 221
Publisher: IEEE
 
» MTT-S Wireless Power Transfer Conference 2017 [Conference Reports]
Abstract:
Presents information on the 2017 MTT-S Wireless Power Transfer Conference.
Autors: Heng-Ming Hsu;
Appeared in: IEEE Microwave Magazine
Publication date: Feb 2018, volume: 19, issue:1, pages: 127 - 128
Publisher: IEEE
 
» Multi-Channel Resource Allocation Toward Ergodic Rate Maximization for Underlay Device-to-Device Communications
Abstract:
In underlay device-to-device (D2D) communications, a D2D pair reuses the cellular spectrum causing interference to regular cellular users. Maximizing the performance of underlay D2D communications requires joint consideration for the achieved D2D rate and the interference to cellular users. In this paper, we consider the D2D power allocation optimization over multiple resource blocks (RBs), aimed at maximizing either the ergodic D2D rate or the ergodic sum rate of D2D and cellular users, under the long-term sum-power constraint of the D2D users and per-RB probabilistic signal-to-interference-and-noise (SINR) requirements for all cellular users. We formulate stochastic optimization problems for D2D power allocation over time. The proposed optimization framework is applicable to both uplink and downlink cellular spectrum sharing. To solve the proposed stochastic optimization problems, we first convexify the problems by introducing a family of convex constraints as a replacement for the non-convex probabilistic SINR constraints. We then present two dynamic power allocation algorithms: a Lagrange dual-based algorithm that is optimal but with a high computational complexity and a low-complexity heuristic algorithm based on dynamic time averaging. Through simulation, we show that the performance gap between the optimal and heuristic algorithms is small, and the effective long-term stochastic D2D power optimization over the shared RBs can lead to substantial gains in the ergodic D2D rate and the ergodic sum rate.
Autors: Ruhallah AliHemmati;Min Dong;Ben Liang;Gary Boudreau;S. Hossein Seyedmehdi;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Feb 2018, volume: 17, issue:2, pages: 1011 - 1025
Publisher: IEEE
 
» Multi-Perspective Tracking for Intelligent Vehicle
Abstract:
The multi-camera array has drawn attention of researchers in recent years, and has been configured and deployed on intelligent vehicle to capture the panoramic views. Understanding surroundings is crucial for the ego-vehicle. This paper presents a Multi-perspective Tracking (MPT) framework for intelligent vehicle. An iterative search procedure is proposed to associate detections and tracklets in different perspectives. This procedure iteratively assigns determined states and estimates non-determined states for the detections and tracklets. An inherent determined and non-determined graph is utilized to reinforce this procedure. For more reliable associations between perspectives, a Siamese convolutional neural network is employed to learn feature representation. The supervised classification and verification signals are added to train the network. The features in different conventional stages are integrated together as the discriminative appearance model. The experiments are conducted on a MPT data set with five perspectives. The proposed framework is tested in each pair of adjacent perspectives for the ability to associate target objects between perspectives.
Autors: Xiangyang Ji;Guanwen Zhang;Xiaogang Chen;Qi Guo;
Appeared in: IEEE Transactions on Intelligent Transportation Systems
Publication date: Feb 2018, volume: 19, issue:2, pages: 518 - 529
Publisher: IEEE
 
» Multi-Rate Acquisition for Dead Time Reduction in Magnetic Resonance Receivers: Application to Imaging With Zero Echo Time
Abstract:
For magnetic resonance imaging of tissues with very short transverse relaxation times, radio-frequency excitation must be immediately followed by data acquisition with fast spatial encoding. In zero-echo-time (ZTE) imaging, excitation is performed while the readout gradient is already on, causing data loss due to an initial dead time. One major dead time contribution is the settling time of the filters involved in signal down-conversion. In this paper, a multi-rate acquisition scheme is proposed to minimize dead time due to filtering. Short filters and high output bandwidth are used initially to minimize settling time. With increasing time since the signal onset, longer filters with better frequency selectivity enable stronger signal decimation. In this way, significant dead time reduction is accomplished at only a slight increase in the overall amount of output data. Multi-rate acquisition was implemented with a two-stage filter cascade in a digital receiver based on a field-programmable gate array. In ZTE imaging in a phantom and in vivo, dead time reduction by multi-rate acquisition is shown to improve image quality and expand the feasible bandwidth while increasing the amount of data collected by only a few percent.
Autors: Josip Marjanovic;Markus Weiger;Jonas Reber;David O. Brunner;Benjamin E. Dietrich;Bertram J. Wilm;Romain Froidevaux;Klaas P. Pruessmann;
Appeared in: IEEE Transactions on Medical Imaging
Publication date: Feb 2018, volume: 37, issue:2, pages: 408 - 416
Publisher: IEEE
 
» Multi-Scale and Frequency-Dependent Modeling of Electric Power Transmission Lines
Abstract:
A frequency-dependent transmission line model for multi-scale simulation of diverse transients over a wide range of frequencies is developed, implemented, and validated. It makes use of the concept of frequency-adaptive simulation of transients in which the Fourier spectra are adaptively shifted in the frequency domain to reduce the discretization time-steps in the time domain. The transients are modeled through dynamic phasors comprising the real and imaginary parts of analytic signals to facilitate the frequency shifting. In the proposed line model, all mathematical operations such as numerical recursive convolutions are, therefore, expressed in terms of analytic signals. A modal decomposition is performed to attain decoupled modes for the multi-phase case. The transition from the representation of electromagnetic traveling waves with time-steps below the wave propagation time to the tracking of slower electromechanical transients at time-steps above the wave propagation time is achieved by the automatic insertion of a -segment to represent the galvanic coupling within one time-step. Accurate and efficient simulation of both electromagnetic and electromechanical transients within a simulation run is so supported. The validation is verified through comparison with a staged field test covering the diverse transients of line energization, transient recovery voltage, and steady state.
Autors: Hua Ye;Kai Strunz;
Appeared in: IEEE Transactions on Power Delivery
Publication date: Feb 2018, volume: 33, issue:1, pages: 32 - 41
Publisher: IEEE
 
» Multi-Scale Segmentation and Surface Fitting for Measuring 3-D Macular Holes
Abstract:
Macular holes are blinding conditions, where a hole develops in the central part of retina, resulting in reduced central vision. The prognosis and treatment options are related to a number of variables, including the macular hole size and shape. High-resolution spectral domain optical coherence tomography allows precise imaging of the macular hole geometry in three dimensions, but the measurement of these by human observers is time-consuming and prone to high inter- and intra-observer variability, being characteristically measured in 2-D rather than 3-D. We introduce several novel techniques to automatically retrieve accurate 3-D measurements of the macular hole, including: surface area, base area, base diameter, top area, top diameter, height, and minimum diameter. Specifically, we introduce a multi-scale 3-D level set segmentation approach based on a state-of-the-art level set method, and we introduce novel curvature-based cutting and 3-D measurement procedures. The algorithm is fully automatic, and we validate our extracted measurements both qualitatively and quantitatively, where our results show the method to be robust across a variety of scenarios. Our automated processes are considered a significant contribution for clinical applications.
Autors: Amar V. Nasrulloh;Chris G. Willcocks;Philip T. G. Jackson;Caspar Geenen;Maged S. Habib;David H. W. Steel;Boguslaw Obara;
Appeared in: IEEE Transactions on Medical Imaging
Publication date: Feb 2018, volume: 37, issue:2, pages: 580 - 589
Publisher: IEEE
 
» Multi-Target Regression via Robust Low-Rank Learning
Abstract:
Multi-target regression has recently regained great popularity due to its capability of simultaneously learning multiple relevant regression tasks and its wide applications in data mining, computer vision and medical image analysis, while great challenges arise from jointly handling inter-target correlations and input-output relationships. In this paper, we propose Multi-layer Multi-target Regression (MMR) which enables simultaneously modeling intrinsic inter-target correlations and nonlinear input-output relationships in a general framework via robust low-rank learning. Specifically, the MMR can explicitly encode inter-target correlations in a structure matrix by matrix elastic nets (MEN); the MMR can work in conjunction with the kernel trick to effectively disentangle highly complex nonlinear input-output relationships; the MMR can be efficiently solved by a new alternating optimization algorithm with guaranteed convergence. The MMR leverages the strength of kernel methods for nonlinear feature learning and the structural advantage of multi-layer learning architectures for inter-target correlation modeling. More importantly, it offers a new multi-layer learning paradigm for multi-target regression which is endowed with high generality, flexibility and expressive ability. Extensive experimental evaluation on 18 diverse real-world datasets demonstrates that our MMR can achieve consistently high performance and outperforms representative state-of-the-art algorithms, which shows its great effectiveness and generality for multivariate prediction.
Autors: Xiantong Zhen;Mengyang Yu;Xiaofei He;Shuo Li;
Appeared in: IEEE Transactions on Pattern Analysis and Machine Intelligence
Publication date: Feb 2018, volume: 40, issue:2, pages: 497 - 504
Publisher: IEEE
 
» Multi-User Computation Offloading in Mobile Edge Computing: A Behavioral Perspective
Abstract:
By providing cloud computing capabilities at the network edge in proximity of mobile device users, mobile edge computing offers an effective solution to help mobile devices with computation- intensive and delay-sensitive tasks. In this article, we investigate the multi-user computation offloading problem in an uncertain wireless environment. Most of the existing works assume that mobile device users are rational and make offloading decisions to maximize their expected objective utilities. However, in practice, users tend to have subjective perceptions under uncertainty, such that their behavior deviates considerably from the conventional rationality assumption. Drawing on the framework of prospect theory (PT), we formulate users' decision making of whether to offload or not as a PT-based non-cooperative game. We propose a distributed computation offloading algorithm to achieve the Nash equilibrium of the game. Numerical results assess the impact of mobile device users' behavioral biases on offloading decision making.
Autors: Ling Tang;Shibo He;
Appeared in: IEEE Network
Publication date: Feb 2018, volume: 32, issue:1, pages: 48 - 53
Publisher: IEEE
 
» Multiagent-Based Flexible Edge Computing Architecture for IoT
Abstract:
This article presents a proposal for FLEC architecture, which solves problems resulting from the rigidity of the traditional IoT architecture and edge computing. FLEC architecture is a flexible and advanced IoT system model characterized by environment adaptation ability and user orientation ability. We utilize COSAP, a system configuration platform based on a multiagent framework, as an implementation procedure for FLEC architecture. Furthermore, this article presents its application case study of a healthcare support system for a sports event with many participants. Finally, we demonstrate the contribution of this proposed architecture to problem solution in edge computing.
Autors: Takuo Suganuma;Takuma Oide;Shinji Kitagami;Kenji Sugawara;Norio Shiratori;
Appeared in: IEEE Network
Publication date: Feb 2018, volume: 32, issue:1, pages: 16 - 23
Publisher: IEEE
 
» Multibeam Focal Plane Arrays With Digital Beamforming for High Precision Space-Borne Ocean Remote Sensing
Abstract:
The present-day ocean remote sensing instruments that operate at low microwave frequencies are limited in spatial resolution and do not allow for monitoring of the coastal waters. This is due to the difficulties of employing a large reflector antenna on a satellite platform, and generating high-quality pencil beams at multiple frequencies. Recent advances in digital beamforming focal-plane arrays (FPAs) have been exploited in this paper to overcome the above problems. A holistic design procedure for such novel multibeam radiometers has been developed, where: 1) the antenna system specifications are derived directly from the requirements to oceanographic surveys for future satellite missions and 2) the numbers of FPA elements/receivers are determined through a dedicated optimum beamforming procedure minimizing the distance to coast. This approach has been applied to synthesize FPAs for two alternative radiometer systems: a conical scanner with an offset parabolic reflector and a stationary wide-scan torus reflector system, each operating at -, -, and Ku-bands. Numerical results predict excellent beam performance for both systems with as low as 0.14% total received power over the land.
Autors: Oleg A. Iupikov;Marianna V. Ivashina;Niels Skou;Cecilia Cappellin;Knud Pontoppidan;Cornelis G. M. van ’t Klooster;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Feb 2018, volume: 66, issue:2, pages: 737 - 748
Publisher: IEEE
 
» Multidevice Map-Constrained Fingerprint-Based Indoor Positioning Using 3-D Ray Tracing
Abstract:
This paper studies the use of deterministic channel modeling through 3-D ray tracing (RT) for constructing device-independent radiomaps for Wi-Fi RSSI-based fingerprinting indoor positioning, applicable to different devices. Device heterogeneity constitutes a limitation in fingerprint-based approaches and also constructing radiomaps through extensive in situ measurement campaigns is laborious and time-consuming even with a single device let alone the need for radiomaps constructed using multiple different devices. This paper tackles both challenges through the use of 3-D RT for radiomap generation in conjunction with data calibration using a small set of device-specific measurements to make the radiomap device independent. The efficiency of this approach is evaluated using simulations and measurements in terms of the time spent to generate the radiomap, the amount of device-specific data required for calibration, and in terms of the achievable positioning accuracy. Potential accuracy improvements in the RT-based indoor positioning process are further investigated, by studying the use of map constraints into the algorithm in the form of a priori probabilities. In this approach, a route probability factor (RPF), which reflects the likelihood of a user being in various locations inside the environment is used. The outcome of the evaluation process, which includes a study of different RPF distributions, indicates the validity of the approach, demonstrated by a reduction in the positioning error for various devices. The versatility of this approach is also demonstrated for different scenarios, different devices, and by considering different device-handling conditions.
Autors: Marios Raspopoulos;
Appeared in: IEEE Transactions on Instrumentation and Measurement
Publication date: Feb 2018, volume: 67, issue:2, pages: 466 - 476
Publisher: IEEE
 
» Multilabel Remote Sensing Image Retrieval Using a Semisupervised Graph-Theoretic Method
Abstract:
Conventional supervised content-based remote sensing (RS) image retrieval systems require a large number of already annotated images to train a classifier for obtaining high retrieval accuracy. Most systems assume that each training image is annotated by a single label associated to the most significant semantic content of the image. However, this assumption does not fit well with the complexity of RS images, where an image might have multiple land-cover classes (i.e., multilabels). Moreover, annotating images with multilabels is costly and time consuming. To address these issues, in this paper, we introduce a semisupervised graph-theoretic method in the framework of multilabel RS image retrieval problems. The proposed method is based on four main steps. The first step segments each image in the archive and extracts the features of each region. The second step constructs an image neighborhood graph and uses a correlated label propagation algorithm to automatically assign a set of labels to each image in the archive by exploiting only a small number of training images annotated with multilabels. The third step associates class labels with image regions by a novel region labeling strategy, whereas the final step retrieves the images similar to a given query image by a subgraph matching strategy. Experiments carried out on an archive of aerial images show the effectiveness of the proposed method when compared with the state-of-the-art RS content-based image retrieval methods.
Autors: Bindita Chaudhuri;Begüm Demir;Subhasis Chaudhuri;Lorenzo Bruzzone;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Feb 2018, volume: 56, issue:2, pages: 1144 - 1158
Publisher: IEEE
 
» Multilayer Millimeter-Wave MCMs [From the Guest Editors' Desk]
Abstract:
After a brief review of the state of the art, this focus issue on multilayer millimeter-wave (mmW) multichip modules (MCMs) presents four cover features that showcase the evolution in some key areas of multilayer mmW MCM integration and packaging technologies: advanced interconnects, integration techniques, components, and systems that use additive as well as substructure manufacturing technologies aimed toward making next-generation mmW applications feasible. The first two features provide an overview of state-of-the-art multilayer ceramic-based multichip module and packaging techniques, while the third and fourth features are more specific: one describing SiP eWLB packaging techniques and the other covering recent developments in inkjet and 3-D printed components and subsystems using additive manufacturing technologies.
Autors: Kamal K. Samanta;Dietmar Kissinger;
Appeared in: IEEE Microwave Magazine
Publication date: Feb 2018, volume: 19, issue:1, pages: 20 - 135
Publisher: IEEE
 
» Multimodal Forecasting Methodology Applied to Industrial Process Monitoring
Abstract:
Industrial process modeling represents a key factor to allow the future generation of industrial manufacturing plants. In this regard, accurate models of critical signals need to be designed in order to forecast process deviations. In this work, a novel multimodal forecasting methodology based on adaptive dynamics packaging and codification of the process operation is proposed. First, a target signal is decomposed by means of the empirical mode decomposition in order to identify the characteristic intrinsic mode functions. Second, such dynamics are packaged depending on their significance and modeling complexity. Third, the operating condition of the considered process, reflected by available auxiliary signals, is codified by means of a self-organizing map and presented to the modeling structure. The forecasting structure is supported by a set of ensemble adaptive-neurofuzzy-inference-system-based models, each one being focused on a different set of signal dynamics. The performance and effectiveness of the proposed method are validated experimentally with industrial data from a copper rod manufacturing plant and performance comparison with classical approaches. The proposed method shows improved performance and generalization over classical single-model approaches.
Autors: Daniel Zurita;Miguel Delgado;Jesus A. Carino;Juan A. Ortega;
Appeared in: IEEE Transactions on Industrial Informatics
Publication date: Feb 2018, volume: 14, issue:2, pages: 494 - 503
Publisher: IEEE
 
» Multimodal Measurements Fusion for Surface Material Categorization
Abstract:
Sound and acceleration measurements are two classes of sensing modalities which frequently occur in surface material categorization. Their fusion problem is extremely important in many practical scenarios, since they provide different properties about materials. In this paper, we investigate the multimodal measurements fusion categorization problem exhibiting nontrivial challenges that there does not exist sample-to-sample pairing relation between sound and acceleration measurements. To this end, we design a dictionary learning model that can simultaneously learn the projection subspace and the latent common dictionary for the different measurements. Furthermore, an optimization algorithm is developed to effectively solve the common dictionary learning problem. Based on the obtained solutions, the fusion categorization algorithm can be easily developed. Finally, we perform experimental validations on the publicly available data set to show the effectiveness of the proposed method.
Autors: Huaping Liu;Fuchun Sun;Bin Fang;Shan Lu;
Appeared in: IEEE Transactions on Instrumentation and Measurement
Publication date: Feb 2018, volume: 67, issue:2, pages: 246 - 256
Publisher: IEEE
 
» Multiobjective Optimization Design for Electrically Large Coverage: Fragment-Type Near-Field/Far-Field UHF RFID Reader Antenna Design
Abstract:
The design of an ultrahigh-frequency (UHF) radio-frequency identification (RFID) reader antenna covering an electrically large near-field area is challenging for near-field UHF RFID applications. In such a design, magnetic field distribution on a large coverage area is required to be as uniform as possible. For some specific UHF near-field RFID applications, given radiation pattern characteristics are expected. A fragment-type wire structure is quite suitable for these demands because uniform magnetic field distribution and given patterns could be generated through optimizing the fragmented wires in a designated electrically large area to obtain corresponding current distribution. In this article, the concept of a fragment-type structure as well as some design guidelines are reviewed and summarized. Then, two omnidirectional fragment-type wire antennas with different cell size and two directional fragment-type wire antennas are designed. Both simulation and experiment results show that there is no reading null within an electrically large near-field zone having a perimeter of four operating wavelengths at 915 MHz (i.e., 320 mm x 320 mm). The omnidirectional designs are promising in the applications of UHF near-field RFID tag detection in self-confined volumes, and the directional designs are potential in the systems of UHF near-field/far-field RFID.
Autors: Dawei Ding;Jing Xia;Lixia Yang;Xiaodong Ding;
Appeared in: IEEE Antennas and Propagation Magazine
Publication date: Feb 2018, volume: 60, issue:1, pages: 27 - 37
Publisher: IEEE
 
» Multipartite Quantum Key Agreement Over Collective Noise Channels
Abstract:
In this paper, two classes of multiparticle entangled states are constructed to resist against the collective-dephasing noise and collective-rotation noise, respectively. Based on it, two new multipartite quantum key agreement protocols over the collective noise are presented. In each protocol, only one user needs to prepare the multiparticle quantum entangled state. Then, the user keeps the first qubit, and distributes each two qubits of the state to other users. In this case, all users can perform the security test and derive the shared key from the measurement outcomes of the qubits in their hands. From the security analysis, it is evident that the presented protocols are secure against the inside attack and some common outside attacks.
Autors: Binbin Cai;Gongde Guo;Song Lin;Huijuan Zuo;Chaohua Yu;
Appeared in: IEEE Photonics Journal
Publication date: Feb 2018, volume: 10, issue:1, pages: 1 - 11
Publisher: IEEE
 
» Multipath Maximum Likelihood Probabilistic Multihypothesis Tracker for Low Observable Targets
Abstract:
In many practical scenarios with multipath propagation, one target may generate multiple detections in one scan. Proper use of multipath-induced measurements can improve the detection of very low observable (VLO) targets. In this paper, a true multitarget tracker, the joint multipath maximum likelihood probabilistic multihypothesis tracker (JMP-ML-PMHT) is proposed to address this problem. The standard ML-PMHT is extended to incorporate multipath detections and jointly track multiple VLO targets. The Cramer–Rao lower bound with multipath detections is derived. Simulation results with an over-the-horizon-radar scenario show that the JMP-ML-PMHT can detect and track multiple VLO targets by effectively utilizing the information in multipath measurements.
Autors: X. Tang;Q. Wu;R. Tharmarasa;T. Kirubarajan;
Appeared in: IEEE Transactions on Aerospace and Electronic Systems
Publication date: Feb 2018, volume: 54, issue:1, pages: 502 - 510
Publisher: IEEE
 
» Multiport Pixel Rectenna for Ambient RF Energy Harvesting
Abstract:
We describe the design of a multiport pixel rectenna for ambient radio-frequency (RF) energy harvesting consisting of an optimized triple-port pixel antenna and a triple-port rectifier with dc combining. The advantages of the multiport pixel approach include enhanced harvested RF power for a given area as well as a reduction in the antenna matching requirements. We formulate the design of the triple-port pixel antenna as a binary optimization problem with an objective function related to harvested RF power in the GSM-1800 band for specified power angular spectrums without the need for antenna matching components. The optimization of the triple-port pixel antenna is obtained by using successive exhaustive Boolean optimization. The design for the triple-port rectifier with dc combining is also provided and a prototype is demonstrated. The rectenna measurement demonstrates that the proposed triple-port pixel antenna has dc output power over double that of single-port-based antennas of similar size. The overall RF-to-dc efficiency of the multiport pixel rectenna is also evaluated and shown to be 19% when the total input RF power is −20 dBm. The effects of nonuniformity in the input RF power across antenna ports are also investigated.
Autors: Shanpu Shen;Chi-Yuk Chiu;Ross D. Murch;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Feb 2018, volume: 66, issue:2, pages: 644 - 656
Publisher: IEEE
 
» Multisensor Data-Fusion-Based Approach to Airspeed Measurement Fault Detection for Unmanned Aerial Vehicles
Abstract:
Fault detection (FD) plays an important role in guaranteeing system safety and reliability for unmanned aerial vehicles (UAVs). This paper focuses on developing an alternative approach to FD for airspeed sensor in UAVs by using data from gyros, accelerometers, global positioning system, and wind vanes. Based on the kinematics model of the UAV, an estimator is proposed to provide analytical redundancy using information from the above-mentioned sensors, which are commonly implemented on UAVs. This filter process is independent of the airspeed measurement and the aircraft dynamics model. Furthermore, we employ the observability rank criterion based on Lie derivatives and prove that the nonlinear system describing the airspeed kinematics is observable. The test and cumulative sum detector are employed to detect the occurrence of airspeed measurement faults together. Finally, the performance of the proposed methodology has been evaluated through flight experiments of UAVs.
Autors: Dingfei Guo;Maiying Zhong;Donghua Zhou;
Appeared in: IEEE Transactions on Instrumentation and Measurement
Publication date: Feb 2018, volume: 67, issue:2, pages: 317 - 327
Publisher: IEEE
 
» Multisource Remote Sensing Data Classification Based on Convolutional Neural Network
Abstract:
As a list of remotely sensed data sources is available, how to efficiently exploit useful information from multisource data for better Earth observation becomes an interesting but challenging problem. In this paper, the classification fusion of hyperspectral imagery (HSI) and data from other multiple sensors, such as light detection and ranging (LiDAR) data, is investigated with the state-of-the-art deep learning, named the two-branch convolution neural network (CNN). More specific, a two-tunnel CNN framework is first developed to extract spectral-spatial features from HSI; besides, the CNN with cascade block is designed for feature extraction from LiDAR or high-resolution visual image. In the feature fusion stage, the spatial and spectral features of HSI are first integrated in a dual-tunnel branch, and then combined with other data features extracted from a cascade network. Experimental results based on several multisource data demonstrate the proposed two-branch CNN that can achieve more excellent classification performance than some existing methods.
Autors: Xiaodong Xu;Wei Li;Qiong Ran;Qian Du;Lianru Gao;Bing Zhang;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Feb 2018, volume: 56, issue:2, pages: 937 - 949
Publisher: IEEE
 
» Multivariate Alarm Systems for Time-Varying Processes Using Bayesian Filters With Applications to Electrical Pumps
Abstract:
Alarm systems are critically important for safety and efficiency of industrial plants. However, many alarm variables in contemporary alarm systems are generated in a way being isolated from related process variables, resulting in false and missing alarms. This paper is motivated by abnormality detection for condensate-water electrical pumps in thermal power plants and proposes a method to design multivariate alarm systems for time-varying processes. A novel feature to distinguish normal and abnormal conditions is observed on the variation rates of multiple linear regression model parameters. A model estimator based on Bayesian filters is formulated to track the variations of model parameters in normal conditions, and not to do so in abnormal conditions so that absolute cumulative modeling errors are large enough to raise alarms. The effectiveness of the proposed method is validated by industrial case studies.
Autors: Wanqi Xiong;Jiandong Wang;Kuang Chen;
Appeared in: IEEE Transactions on Industrial Informatics
Publication date: Feb 2018, volume: 14, issue:2, pages: 504 - 513
Publisher: IEEE
 
» Multiview Intensity-Based Active Learning for Hyperspectral Image Classification
Abstract:
In remote sensing image classification, active learning aims to learn a good classifier as best as possible by choosing the most valuable (informative and representative) training samples. Multiview is a concept that regards analyzing the same object from multiple different views. Generally, these views show diversity and complementarity of features. In this paper, we propose a new multiview active learning (MVAL) framework for hyperspectral image classification. First, we generate multiple views by extracting different attribute components from the same image data. Specifically, we adopt the multiple morphological component analysis to decompose the original image into multiple pairs of attribute components, including content, coarseness, contrast, and directionality, and the smooth component from each pair is chosen as one single view. Second, we construct two multiview intensity-based query strategies for active learning. On the one hand, we exploit the intensity differences of multiple views along with the samples’ uncertainty to choose the most informative candidates. On the other hand, we consider the clustering distribution of all unlabeled samples, and query the most representative candidates in addition to the highly informative ones. Our experiments are performed on four benchmark hyperspectral image data sets. The obtained results show that the proposed MVAL framework can lead to better classification performance than the traditional, single-view active learning schemes. In addition, compared with the conventional disagree-based MVAL scheme, the proposed query selection strategies show competitive classification accuracy.
Autors: Xiang Xu;Jun Li;Shutao Li;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Feb 2018, volume: 56, issue:2, pages: 669 - 680
Publisher: IEEE
 
» Multiview Rectification of Folded Documents
Abstract:
Digitally unwrapping images of paper sheets is crucial for accurate document scanning and text recognition. This paper presents a method for automatically rectifying curved or folded paper sheets from a few images captured from multiple viewpoints. Prior methods either need expensive 3D scanners or model deformable surfaces using over-simplified parametric representations. In contrast, our method uses regular images and is based on general developable surface models that can represent a wide variety of paper deformations. Our main contribution is a new robust rectification method based on ridge-aware 3D reconstruction of a paper sheet and unwrapping the reconstructed surface using properties of developable surfaces via conformal mapping. We present results on several examples including book pages, folded letters and shopping receipts.
Autors: Shaodi You;Yasuyuki Matsushita;Sudipta Sinha;Yusuke Bou;Katsushi Ikeuchi;
Appeared in: IEEE Transactions on Pattern Analysis and Machine Intelligence
Publication date: Feb 2018, volume: 40, issue:2, pages: 505 - 511
Publisher: IEEE
 
» Multiyear Trans-Horizon Radio Propagation Measurements at 3.5 GHz
Abstract:
The design, realization, and measurement results of a high-accuracy multiyear 3.5 GHz trans-horizon radio propagation measurement system are discussed, with both emphasis on the results and implemented technical measures to enhance the accuracy and overall reliability of the measurements. The propagation measurements have been performed on two different paths of 253 and 234 km length, using two transmitters and one receiver in the period September 2013 till November 2016. One of the paths travels over wetland; the other path can be considered as a land path. On each path, an additional transmitter is placed at 107 km (in the 253 km path) and 84 km (in the 234 km path) from the receiver. With this arrangement, the correlation between two nonaligned paths of comparable length, and two aligned paths of dissimilar length, was studied. The measurements show that for the land path, the predicted ITU-R P.452-16 cumulative distribution function (CDF) typically shows 5 dB higher path loss than the actual measured CDF for the region of interest; anomalous propagation. This means that the measured signal is on average weaker than predicted (a higher path loss). For the wetland path, the actual CDF is very close to the predicted CDF. Also, the measurements reveal that typically 30% of the anomalous propagation occurrences are correlated with other paths.
Autors: Loek C. Colussi;Roel Schiphorst;Herman W. M. Teinsma;Ben A. Witvliet;Sjoert R. Fleurke;Mark J. Bentum;Erik van Maanen;Johan Griffioen;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Feb 2018, volume: 66, issue:2, pages: 884 - 896
Publisher: IEEE
 
» MV Generator Ground Fault Arcing Power Damage Assessment
Abstract:
An industrial medium voltage (MV) system usually consists of multiple power sources such as utility tie transformers and generators. These are normally low-resistance grounding as shown in Fig. 1 . When a ground fault occurs at the generator stator, ground currents from its own neutral circuit and external power sources will flow into the fault and cause damages to the stator winding. The IEEE Generator Grounding Working Group issued a guideline for generator grounding practices, which recommends using a hybrid grounding system to minimize the ground fault damage induced by its own neutral grounding source. This paper will evaluate the total ground fault damages based on the arcing power energy to derive a maximum MV system ground current that would limit the ground damage to 1800 kW-cycle or 30 kJ as the minimum arcing power energy damage as suggested by Conrad and Dalasta [10].
Autors: Alex Y. Wu;
Appeared in: IEEE Transactions on Industry Applications
Publication date: Feb 2018, volume: 54, issue:1, pages: 912 - 915
Publisher: IEEE
 
» Nanocrystalline Silicon Lateral MSM Photodetector for Infrared Sensing Applications
Abstract:
A novel lateral nanocrystalline silicon (nc-Si) metal–semiconductor–metal photodetector architecture is proposed using an organic blocking layer. Fabricated devices exhibit low dark current, high dynamic range, and a measured external quantum efficiency approaching 35% at 740 nm and 15% at 850 nm. The higher performance is enabled by integrating an nc-Si film with a previously reported thin organic polyimide blocking layer and subsequently operating at high electric fields. Unlike industry standard p-i-n photodiodes, our high-performance lateral photosensor does not require doped p+ and n+ layers. Thus, the reported device is compatible with industrial standard amorphous silicon thin-film transistor display fabrication process, making it promising for large-area biometric full-hand imaging applications.
Autors: Muhammad A. Martuza;Sina Ghanbarzadeh;Czang-Ho Lee;Celal Con;Karim S. Karim;
Appeared in: IEEE Transactions on Electron Devices
Publication date: Feb 2018, volume: 65, issue:2, pages: 584 - 590
Publisher: IEEE
 
» Naturalness Preserved Nonuniform Illumination Estimation for Image Enhancement Based on Retinex
Abstract:
Illumination estimation is important for image enhancement based on Retinex. However since illumination estimation is an ill-posed problem it is difficult to achieve accurate illumination estimation for nonuniform illumination images. The conventional illumination estimation algorithms fail to comprehensively take all the constraints into the consideration such as spatial smoothness sharp edges on illumination boundaries and limited range of illumination. Thus these algorithms cannot effectively and efficiently estimate illumination while preserving naturalness. In this paper we present a naturalness preserved illumination estimation algorithm based on the proposed joint edge-preserving filter which exploits all the abovementioned constraints. Moreover a fast estimation is implemented based on the box filter. Experimental results demonstrate that the proposed algorithm can achieve the adaptive smoothness of illumination beyond edges and ensure the range of the estimated illumination. When compared with other state-of-the-art algorithms it can achieve better quality from both subjective and objective aspects.
Autors: Yuanyuan Gao;Hai-Miao Hu;Bo Li;Qiang Guo;
Appeared in: IEEE Transactions on Multimedia
Publication date: Feb 2018, volume: 20, issue:2, pages: 335 - 344
Publisher: IEEE
 
» Nature of Sideband Generation
Abstract:
The serious investigation of sidebands (SBs), which are the result of nonlinear processes, began in the late 19th century when research was being conducted on amplitude modulation (Panter, 1965). In 1875, A.M. Mayer experimentally proved the existence of SBs. In 1886, M. Leblanc was likely the first to amplitude modulate a carrier signal with speech. Later, in 1894, Lord Rayleigh theoretically demonstrated the existence of SBs.
Autors: Don E. Czyzyk;
Appeared in: IEEE Potentials
Publication date: Feb 2018, volume: 37, issue:1, pages: 19 - 22
Publisher: IEEE
 
» Near-Field VLF Electromagnetic Signal Propagation in Multistory Buildings
Abstract:
In this paper, we present modeling of very low frequency (3–30 kHz) through-the-Earth (TTE) radio transmissions in four multistory buildings using the finite-difference time-domain method. These structures are generally made of reinforced concrete, whose steel content is the most important control on bulk conductivity. The floors and walls are represented as sheets of a given conductance, based on the fact that electromagnetic geophysical methods will only resolve conductive sheets in terms of their conductance as opposed to both conductivity and thickness. We validate this approach first using synthetic data and second by comparison with field data. Conductance models were derived from observed data for a variety of propagation environments, including reinforced concrete, steel floors, and basements, and for transmission into, out of, or within a building. The models were able to account for nonintuitive observations, such as increase in signal strength near the edges of buildings and in localized areas in between buildings. Conductances obtained for the floors and walls could be used as representative values in future forward modeling to assess the viability or optimize a TTE radio link in a multistory building.
Autors: Maxim Ralchenko;Mike Roper;Claire Samson;Markus Svilans;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Feb 2018, volume: 66, issue:2, pages: 848 - 856
Publisher: IEEE
 
» Negative Capacitance Carbon Nanotube FETs
Abstract:
As continued scaling of silicon FETs grows increasingly challenging, alternative paths for improving digital system energy efficiency are being pursued. These paths include replacing the transistor channel with emerging nanomaterials (such as carbon nanotubes), as well as utilizing negative capacitance effects in ferroelectric materials in the FET gate stack, e.g., to improve sub-threshold slope beyond the 60 mV/decade limit. However, which path provides the largest energy efficiency benefits—and whether these multiple paths can be combined to achieve additional energy efficiency benefits—is still unclear. Here, we experimentally demonstrate the first negative capacitance carbon nanotube FETs (CNFETs), combining the benefits of both carbon nanotube channels and negative capacitance effects. We demonstrate negative capacitance CNFETs, achieving sub-60 mV/decade sub-threshold slope with an average sub-threshold slope of 55 mV/decade at room temperature. The average ON-current () of these negative capacitance CNFETs improves by versus baseline CNFETs, (i.e., without negative capacitance) for the same OFF-current (). This work demonstrates a promising path forward for future generations of energy-efficient electronic systems.
Autors: Tathagata Srimani;Gage Hills;Mindy D. Bishop;Ujwal Radhakrishna;Ahmad Zubair;Rebecca S. Park;Yosi Stein;Tomas Palacios;Dimitri Antoniadis;Max M. Shulaker;
Appeared in: IEEE Electron Device Letters
Publication date: Feb 2018, volume: 39, issue:2, pages: 304 - 307
Publisher: IEEE
 
» Negative Iris Recognition
Abstract:
Elements of a person's biometrics are typically stable over the duration of a lifetime, and thus, it is highly important to protect biometric data while supporting recognition (it is also called secure biometric recognition). However, the biometric data that are derived from a person usually vary slightly due to a variety of reasons, such as distortion during picture capture, and it is difficult to use traditional techniques, such as classical encryption algorithms, in secure biometric recognition. The negative database (NDB) is a new technique for privacy preservation. Reversing the NDB has been demonstrated to be an NP-hard problem, and several algorithms for generating hard-to-reverse NDBs have been proposed. In this paper, first, we propose negative iris recognition, which is a novel secure iris recognition scheme that is based on the NDB. We show that negative iris recognition supports several important strategies in iris recognition, e.g., shifting and masking. Next, we analyze the security and efficiency of negative iris recognition. Experimental results show that negative iris recognition is an effective and secure iris recognition scheme. Specifically, negative iris recognition can achieve a highly promising recognition performance (i.e., GAR = 98.94% at FAR = 0.01%, EER = 0.60%) on the typical database CASIA-IrisV3-Interval.
Autors: Dongdong Zhao;Wenjian Luo;Ran Liu;Lihua Yue;
Appeared in: IEEE Transactions on Dependable and Secure Computing
Publication date: Feb 2018, volume: 15, issue:1, pages: 112 - 125
Publisher: IEEE
 
» Negative Resistance-Based Electronic Impedance Tuner
Abstract:
An electronic impedance tuner using the negative resistance of tunneling diodes is proposed in this paper. Aside from the fact that it is an interesting solution to synthesize impedance with reflection coefficient larger than one, this scheme is proven to be simpler and consume less power than the state-of-the-art techniques. The overall circuit topology consists of two parts, namely, impedance tuning circuit including a hybrid block of PIN and tunneling diode for generating a set of impedance points, and wideband nonlinear transmission line-based 360° phase shifter for rotating the set of impedance points around the Smith chart from 1.5 to 5 GHz. The operating power of the electronic tuner is below −25 dBm, which is limited by the tunneling diode. The worst-case maximum power consumption of the electronic tuner is as low as 3 mW. Such an electronic tuner should be useful for the development of on-wafer noise characterization systems.
Autors: Y. Zhao;S. Hemour;T. Liu;K. Wu;
Appeared in: IEEE Microwave and Wireless Components Letters
Publication date: Feb 2018, volume: 28, issue:2, pages: 144 - 146
Publisher: IEEE
 
» Neuro-Inspired Computing With Emerging Nonvolatile Memorys
Abstract:
This comprehensive review summarizes state of the art, challenges, and prospects of the neuro-inspired computing with emerging nonvolatile memory devices. First, we discuss the demand for developing neuro-inspired architecture beyond today’s von-Neumann architecture. Second, we summarize the various approaches to designing the neuromorphic hardware (digital versus analog, spiking versus nonspiking, online training versus offline training) and discuss why emerging nonvolatile memory is attractive for implementing the synapses in the neural network. Then, we discuss the desired device characteristics of the synaptic devices (e.g., multilevel states, weight update nonlinearity/asymmetry, variation/noise), and survey a few representative material systems and device prototypes reported in the literature that show the analog conductance tuning. These candidates include phase change memory, resistive memory, ferroelectric memory, floating-gate transistors, etc. Next, we introduce the crossbar array architecture to accelerate the weighted sum and weight update operations that are commonly used in the neuro-inspired machine learning algorithms, and review the recent progresses of array-level experimental demonstrations for pattern recognition tasks. In addition, we discuss the peripheral neuron circuit design issues and present a device-circuit-algorithm codesign methodology to evaluate the impact of nonideal device effects on the system-level performance (e.g., learning accuracy). Finally, we give an outlook on the customization of the learning algorithms for efficient hardware implementation.
Autors: Shimeng Yu;
Appeared in: Proceedings of the IEEE
Publication date: Feb 2018, volume: 106, issue:2, pages: 260 - 285
Publisher: IEEE
 
» Neurostream: Scalable and Energy Efficient Deep Learning with Smart Memory Cubes
Abstract:
High-performance computing systems are moving towards 2.5D and 3D memory hierarchies, based on High Bandwidth Memory (HBM) and Hybrid Memory Cube (HMC) to mitigate the main memory bottlenecks. This trend is also creating new opportunities to revisit near-memory computation. In this paper, we propose a flexible processor-in-memory (PIM) solution for scalable and energy-efficient execution of deep convolutional networks (ConvNets), one of the fastest-growing workloads for servers and high-end embedded systems. Our co-design approach consists of a network of Smart Memory Cubes (modular extensions to the standard HMC) each augmented with a many-core PIM platform called NeuroCluster. NeuroClusters have a modular design based on NeuroStream coprocessors (for Convolution-intensive computations) and general-purpose RISC-V cores. In addition, a DRAM-friendly tiling mechanism and a scalable computation paradigm are presented to efficiently harness this computational capability with a very low programming effort. NeuroCluster occupies only 8 percent of the total logic-base (LoB) die area in a standard HMC and achieves an average performance of 240 GFLOPS for complete execution of full-featured state-of-the-art (SoA) ConvNets within a power budget of 2.5 W. Overall 11 W is consumed in a single SMC device, with 22.5 GFLOPS/W energy-efficiency which is 3.5X better than the best GPU implementations in similar technologies. The minor increase in system-level power and the negligible area increase make our PIM system a cost-effective and energy efficient solution, easily scalable to 955 GFLOPS with a small network of just four SMCs.
Autors: Erfan Azarkhish;Davide Rossi;Igor Loi;Luca Benini;
Appeared in: IEEE Transactions on Parallel and Distributed Systems
Publication date: Feb 2018, volume: 29, issue:2, pages: 420 - 434
Publisher: IEEE
 
» New Constructions of Binary and Ternary Locally Repairable Codes Using Cyclic Codes
Abstract:
New constructions of binary and ternary locally repairable codes (LRCs) using cyclic codes and their concatenation are proposed. The proposed binary LRCs with and some and with and some are shown to be optimal in terms of the upper bounds. In addition, the similar method of the binary case is applied to construct the ternary LRCs with good parameters.
Autors: Chanki Kim;Jong-Seon No;
Appeared in: IEEE Communications Letters
Publication date: Feb 2018, volume: 22, issue:2, pages: 228 - 231
Publisher: IEEE
 
» New Constructions of Optimal Locally Recoverable Codes via Good Polynomials
Abstract:
In recent literature, a family of optimal linear locally recoverable codes (LRC codes) that attain the maximum possible distance (given code length, cardinality, and locality) is presented. The key ingredient for constructing such optimal linear LRC codes is the so-called -good polynomials, where is equal to the locality of the LRC code. However, given a prime , known constructions of -good polynomials over some extension field of exist only for some special integers , and the problem of constructing optimal LRC codes over small field for any given locality is still open. In this paper, by using function composition, we present two general methods of designing good polynomials, which lead to three new constructions of -good polynomials. Such polynomials bring new constructions of optimal LRC codes. In particular, our constructed polynomials as well as the power functions yield optimal LRC codes over for all positive integers as localities, where is near the code length .
Autors: Jian Liu;Sihem Mesnager;Lusheng Chen;
Appeared in: IEEE Transactions on Information Theory
Publication date: Feb 2018, volume: 64, issue:2, pages: 889 - 899
Publisher: IEEE
 
» New Heights for Satellites: LTCC Multilayer Technology for Future Satellites
Abstract:
Over the past few years, the demands on satellite communication have undergone significant changes, and, as a consequence, its technologies and system designs are also changing in important ways. Since the introduction of high-definition television, classical geostationary (GEO) satellites in orbit at 36,800 km must transmit higher data rates. Also, GEO satellites are increasingly used for global data transfer, e.g., for Internet applications and business communication. As a consequence, higher-frequency bandwidth, higher transmitting frequencies in the millimeter-wave range, and efficient frequency reuse are needed [1].
Autors: Ingo Wolff;Carsten Günner;Jürgen Kassner;Reinhard Kulke;Peter Uhlig;
Appeared in: IEEE Microwave Magazine
Publication date: Feb 2018, volume: 19, issue:1, pages: 36 - 47
Publisher: IEEE
 
» New Mobility Model for Accurate Modeling of Transconductance in FDSOI MOSFETs
Abstract:
Anomalous transconductance with nonmono- tonic back-gate bias dependence observed in the fully depleted silicon-on-insulator (FDSOI) MOSFET with thick front-gate oxide is discussed. It is found that the anomalous transconductance is attributed to the domination of the back-channel charge in the total channel charge. This behavior is modeled with a novel two-mobility model, which separates the mobility of the front and back channels. These two mobilities are physically related by a charge-based weighting function. The proposed model is incorporated into BSIM-IMG and is in good agreement with the experimental and simulated data of FDSOI MOSFETs for various front-gate oxides, body thicknesses, and gate lengths.
Autors: Yen-Kai Lin;Pragya Kushwaha;Juan Pablo Duarte;Huan-Lin Chang;Harshit Agarwal;Sourabh Khandelwal;Angada B. Sachid;Michael Harter;Josef Watts;Yogesh Singh Chauhan;Sayeef Salahuddin;Chenming Hu;
Appeared in: IEEE Transactions on Electron Devices
Publication date: Feb 2018, volume: 65, issue:2, pages: 463 - 469
Publisher: IEEE
 
» New Models for the Calibration of Four-Channel Time-Interleaved ADCs Using Filter Banks
Abstract:
New linear models to calibrate four-channel time-interleaved analog-to-digital converters are proposed and investigated. The ideal four-periodic correction filters, which cancel distortions, are computed as a function of the error filters that model the analog transfer function of each channel, including the sampling time. These correction filters are then approximated as a linear combination of base filters and new accurate models with a limited number of free parameters are proposed. Calibration is performed using the recursive least squares algorithm to estimate the coefficients of the linear combination (and the offset term). The resulting algorithms are tested for accuracy, convergence speed, and stability in a fixed-point implementation, and are compared with previously published linear background calibration techniques. The proposed filter bank significantly improves the accuracy/complexity tradeoff with respect to previously published techniques.
Autors: Pietro Monsurrò;Felice Rosato;Alessandro Trifiletti;
Appeared in: IEEE Transactions on Circuits and Systems II: Express Briefs
Publication date: Feb 2018, volume: 65, issue:2, pages: 141 - 145
Publisher: IEEE
 
» New Negative Coupling Structure for ${K}$ -Band Substrate-Integrated Waveguide Resonator Filter With a Pair of Transmission Zeros
Abstract:
In this letter, we present a new negative coupling structure applicable to a substrate-integrated waveguide (SIW) resonator filter structure. Unlike conventional negative coupling structure, the proposed coupling structure can achieve a negative coupling value without employing an additional substrate or slots on ground planes. To demonstrate the new negative coupling structure, we designed, fabricated, and measured a fourth-order -band SIW resonator filter with a pair of transmission zeros.
Autors: Boyoung Lee;Seunggoo Nam;Changsoo Kwak;Juseop Lee;
Appeared in: IEEE Microwave and Wireless Components Letters
Publication date: Feb 2018, volume: 28, issue:2, pages: 135 - 137
Publisher: IEEE
 
» New products
Abstract:
Provides various new product announcements.
Autors: Robert Goldberg;
Appeared in: IEEE Instrumentation & Measurement Magazine
Publication date: Feb 2018, volume: 21, issue:1, pages: 63 - 67
Publisher: IEEE
 
» New SMC Materials for Small Electrical Machine With Very Good Mechanical Properties
Abstract:
A new technology may be proposed for the realization of the magnetic parts of electromechanical devices, mainly for small electric machines. Such a technology provides the substitution of the traditional magnetic sheets with parts obtained by molding special magnetic powders [soft magnetic composites (SMC)]. The advantages may be constituted not only by economical reasons, but mostly by the possibility to realize parts having shapes otherwise impossible with the traditional lamination. Some commercial products are available in the market as “ready to press” powders, but their mechanical properties are in general not sufficient. To investigate the possibility to obtain good mechanical properties maintaining the magnetic characteristics of a selected commercial insulated iron powder compound, the authors have conducted a research activity based on the use of special iron powders and a selected epoxy resin as binder. The paper describes the activity carried out for the realization of SMC by mixing iron powders and Epoxy resin with different binder percentages and molding pressures. The obtained results have to be considered very satisfactory and suggest to continue the research argument to explore the possibilities of further improvements.
Autors: Marco Actis Grande;Luca Ferraris;Fausto Franchini;Emir Pošković;
Appeared in: IEEE Transactions on Industry Applications
Publication date: Feb 2018, volume: 54, issue:1, pages: 195 - 203
Publisher: IEEE
 
» New Version of “PaWaIC” Helix-TWT Particle-Wave Interaction Code Based on Pseudospectral Analytical Time-Domain Technique With Collocated Space and Time-Marching Scheme: “PaWaIC-PSATD-CSaT”
Abstract:
Pseudospectral solvers (i.e., demonstrating equations in spatial Fourier domain) have extraordinary accuracy that makes them attractive in numerical modeling research. In this paper, we introduce a new and efficient version of recently introduced code “PaWaIC” based on pseudospectral analytical time-domain implementation named “PaWaIC-PSATD-CSaT. ” This new code is validated by a traveling wave tube product measurement results and the previous version code “PaWaIC-PSAOFDTD” (with pseudospectral arbitrary-order accurate temporal and spatial derivatives finite-difference time-domain technique). We show that for a unique grid cell size and time step length, the new code PaWaIC-PSATD-CSaT realizes the phase velocity of the tube better than the earlier version PaWaIC-PSAOFDTD while still has a fast simulation time. As well, we demonstrate the ability of the new code for pulse amplification response of wideband tubes by a single-run simulation.
Autors: Amir Setayesh;Mohammad Sadegh Abrishamian;
Appeared in: IEEE Transactions on Electron Devices
Publication date: Feb 2018, volume: 65, issue:2, pages: 716 - 723
Publisher: IEEE
 
» New Year, continuing the journey [President's Message]
Abstract:
Greetings and best wishes for a happy and prosperous new year from the Instrumentation and Measurement Society! As engineers we often are faced with problems, and our first step is to assess the resources available to help us solve them. The IEEE Instrumentation and Measurement Society (IMS) faces many of the same pressures and problems of the IEEE as a whole. As the new President of the IMS, I am greatly encouraged by the resources we have to solve them. It amazes me that people of such high caliber are dedicated enough to their profession to volunteer significant amounts of their valuable time. As members of the IMS, you have elected some wonderful people to provide leadership on the Administrative Committee (AdCom). I am truly honored to be serving as President of your society in 2018, and I believe I am well equipped through the talent on the AdCom to address our needs as a profession.
Autors: J. Max Cortner;
Appeared in: IEEE Instrumentation & Measurement Magazine
Publication date: Feb 2018, volume: 21, issue:1, pages: 3 - 3
Publisher: IEEE
 
» No Overlength Page Charges for One Page of References
Abstract:
The IEEE Transactions on Antennas and Propagation (TAP) has changed its editorial policy by allowing one free page of references, i.e., one page that does not incur overlength page charges, provided that such a page is used only for references.
Autors: Danilo Erricolo;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Feb 2018, volume: 66, issue:2, pages: 531 - 532
Publisher: IEEE
 
» Noise Adaptive Kalman Filter for Joint Polarization Tracking and Channel Equalization Using Cascaded Covariance Matching
Abstract:
We propose a noise adaptive Kalman filter for joint polarization tracking and channel equalization using cascaded covariance matching. With the process noise covariance (Q) and the measurement noise covariance (R) estimated in a cascaded manner, the proposed Kalman filter scheme can be implemented in adaptive mode. The experimental results demonstrate that in wide range of OSNR and polarization rotation, the scheme can adaptively configure noise covariance parameters and consequently can achieve optimal performance even in long transmission cases. Besides, the scheme is more robust against the initial errors in Q and R compared to nonadaptive filter and R /Q-adaptive algorithms with the allowable initial values of Q and R within 6 and 9 magnitudes, respectively.
Autors: Qun Zhang;Yanfu Yang;Qian Xiang;Qianwen He;Zhongqing Zhou;Yong Yao;
Appeared in: IEEE Photonics Journal
Publication date: Feb 2018, volume: 10, issue:1, pages: 1 - 11
Publisher: IEEE
 
» Noise Performance Comparison Between Continuous Wave and Stroboscopic Pulse Ground Penetrating Radar
Abstract:
Although stroboscopic pulse (SP) ground penetrating radar (GPR) is the most popular and widespread equipment for subsoil investigation, continuous-wave (CW) radar has better performance in terms of noise, system dynamic range, and penetration depth, at the expense of greater complexity and cost of the components. The aim of this letter is a direct comparison between SP GPR and CW GPR through an extensive measurement campaign in five different locations representative of the different conditions where a GPR could operate.
Autors: Massimiliano Pieraccini;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Feb 2018, volume: 15, issue:2, pages: 222 - 226
Publisher: IEEE
 
» Noise Reduction of Swept-Source Optical Coherence Tomography via Compressed Sensing
Abstract:
In this paper, we investigate noise reduction in swept-source optical coherence tomography (OCT) using compressed sensing (CS). Multiple scan averaging is a classical method used to enhance the quality of OCT images by reducing the noise of a system. However, the conventional averaging method requires a repetitive scan at the same location and thus reduces the imaging speed. In this paper, the sparsity property of an OCT A-scan is utilized, and one full A-scan OCT image can be reconstructed from a portion of the acquired data during one sweep period using CS. Thus, multiple OCT A-scans can be reconstructed from a single sweep. The average A-scans yield a better quality than the single A-scan obtained from the whole data acquired during a sweep period. We demonstrate that the average of five reconstructed A-scans from a single sweep using CS offers an image quality and depth resolution similar to those obtained by averaging three sequential A-scans from three sweeps using the conventional averaging method. This proposed method can shorten the time required to perform repetitive scans and thus improve the imaging speed.
Autors: Site Luo;Qiang Guo;Hui Zhao;Xin An;Liang Zhou;Huikai Xie;Jianyu Tang;Xiao Wang;Hongwei Chen;Li Huo;
Appeared in: IEEE Photonics Journal
Publication date: Feb 2018, volume: 10, issue:1, pages: 1 - 9
Publisher: IEEE
 
» Non-Rigid Event-by-Event Continuous Respiratory Motion Compensated List-Mode Reconstruction for PET
Abstract:
Respiratory motion during positron emission tomography (PET)/computed tomography (CT) imaging can cause significant image blurring and underestimation of tracer concentration for both static and dynamic studies. In this paper, with the aim to eliminate both intra-cycle and inter-cycle motions, and apply to dynamic imaging, we developed a non-rigid event-by-event (NR-EBE) respiratory motion-compensated list-mode reconstruction algorithm. The proposed method consists of two components: the first component estimates a continuous non-rigid motion field of the internal organs using the internal–external motion correlation. This continuous motion field is then incorporated into the second component, non-rigid MOLAR (NR-MOLAR) reconstruction algorithm to deform the system matrix to the reference location where the attenuation CT is acquired. The point spread function (PSF) and time-of-flight (TOF) kernels in NR-MOLAR are incorporated in the system matrix calculation, and therefore are also deformed according to motion. We first validated NR-MOLAR using a XCAT phantom with a simulated respiratory motion. NR-EBE motion-compensated image reconstruction using both the components was then validated on three human studies injected with 18F-FPDTBZ and one with 18F-fluorodeoxyglucose (FDG) tracers. The human results were compared with conventional non-rigid motion correction using discrete motion field (NR-discrete, one motion field per gate) and a previously proposed rigid EBE motion-compensated image reconstruction (R-EBE) that was designed to correct for rigid motion on a target lesion/organ. The XCAT results demonstrated that NR-MOLAR incorporating both PSF and TOF kernels effectively corrected for non-rigid motion. The 18F-FPDTBZ studies showed that NR-EBE out-performed NR-Discrete, and yielded comparable results with R-EBE on target organs while yielding superior image quality in other regions. The FDG study showed that NR- EBE clearly improved the visibility of multiple moving lesions in the liver where some of them could not be discerned in other reconstructions, in addition to improving quantification. These results show that NR-EBE motion-compensated image reconstruction appears to be a promising tool for lesion detection and quantification when imaging thoracic and abdominal regions using PET.
Autors: Chung Chan;John Onofrey;Yiqiang Jian;Mary Germino;Xenophon Papademetris;Richard E. Carson;Chi Liu;
Appeared in: IEEE Transactions on Medical Imaging
Publication date: Feb 2018, volume: 37, issue:2, pages: 504 - 515
Publisher: IEEE
 
» Non-Uniform Wavelet Sampling for RF Analog-to-Information Conversion
Abstract:
Feature extraction, such as spectral occupancy, interferer energy and type, or direction-of-arrival, from wideband radio-frequency (RF) signals finds use in a growing number of applications as it enhances RF transceivers with cognitive abilities and enables parameter tuning of traditional RF chains. In power and cost limited applications, e.g., for sensor nodes in the Internet of Things, wideband RF feature extraction with conventional, Nyquist-rate analog-to-digital converters is infeasible. However, the structure of many RF features (such as signal sparsity) enables the use of compressive sensing (CS) techniques that acquire such signals at sub-Nyquist rates; while such CS-based analog-to-information (A2I) converters have the potential to enable low-cost and energy-efficient wideband RF sensing, they suffer from a variety of real-world limitations, such as noise folding, low sensitivity, aliasing, and limited flexibility. This paper proposes a novel CS-based A2I architecture called non-uniform wavelet sampling. Our solution extracts a carefully-selected subset of wavelet coefficients directly in the RF domain, which mitigates the main issues of existing A2I converter architectures. For multi-band RF signals, we propose a specialized variant called non-uniform wavelet bandpass sampling (NUWBS), which further improves sensitivity and reduces hardware complexity by leveraging the multi-band signal structure. We use simulations to demonstrate that NUWBS approaches the theoretical performance limits of -norm-based sparse signal recovery. We investigate hardware-design aspects and show ASIC measurement results for the wavelet generation stage, which highlight the efficacy of NUWBS for a broad range of RF feature extraction tasks in cost- and power-limited applications.
Autors: Michaël Pelissier;Christoph Studer;
Appeared in: IEEE Transactions on Circuits and Systems I: Regular Papers
Publication date: Feb 2018, volume: 65, issue:2, pages: 471 - 484
Publisher: IEEE
 
» Nonbinary Tree-Based Phylogenetic Networks
Abstract:
Rooted phylogenetic networks are used to describe evolutionary histories that contain non-treelike evolutionary events such as hybridization and horizontal gene transfer. In some cases, such histories can be described by a phylogenetic base-tree with additional linking arcs, which can, for example, represent gene transfer events. Such phylogenetic networks are called tree-based. Here, we consider two possible generalizations of this concept to nonbinary networks, which we call tree-based and strictly-tree-based nonbinary phylogenetic networks. We give simple graph-theoretic characterizations of tree-based and strictly-tree-based nonbinary phylogenetic networks. Moreover, we show for each of these two classes that it can be decided in polynomial time whether a given network is contained in the class. Our approach also provides a new view on tree-based binary phylogenetic networks. Finally, we discuss two examples of nonbinary phylogenetic networks in biology and show how our results can be applied to them.
Autors: Laura Jetten;Leo van Iersel;
Appeared in: IEEE/ACM Transactions on Computational Biology and Bioinformatics
Publication date: Feb 2018, volume: 15, issue:1, pages: 205 - 217
Publisher: IEEE
 
» Nonlinear Characterization for Microstrip Circuits With Low Passive Intermodulation
Abstract:
Products of passive intermodulation (PIM) generated by weak nonlinearities of passive circuits subjected to relatively high transmit power of multicarrier signals may cause strong interference in emerging broadband and multiradio communication systems. This paper presents a new approach to a characterization of distributed nonlinearities in printed circuits fabricated on commercial grade microwave laminate materials. An efficient procedure for PIM characterization has been devised using the commercial RF-CAD software. The phenomenological model has been developed to take into account concurrent distributed nonlinearities of printed transmission lines and to evaluate PIM products of arbitrary order. It has been observed for the first time that the sources of nonlinearity in typical microstrip circuits may have highly uneven distributions which require a different means for PIM characterization and modeling. The proposed methodology has been validated by accurate predictions of the PIM response of complex circuit layouts. The results of this paper pave the way to a holistic approach to the design of planar microwave circuits and devices under given linearity constraints.
Autors: Alexey P. Shitvov;Dmitry S. Kozlov;Alexander G. Schuchinsky;
Appeared in: IEEE Transactions on Microwave Theory and Techniques
Publication date: Feb 2018, volume: 66, issue:2, pages: 865 - 874
Publisher: IEEE
 
» Nonlinear Hyperspectral Unmixing Based on Geometric Characteristics of Bilinear Mixture Models
Abstract:
Recently, many nonlinear spectral unmixing algorithms that use various bilinear mixture models (BMMs) have been proposed. However, the high computational complexity and intrinsic collinearity between true endmembers and virtual endmembers considerably decrease these algorithms’ unmixing performances. In this paper, we come up with a novel abundance estimation algorithm based on the BMMs. Motivated by BMMs’ geometric characteristics that are related to collinearity, we conduct a unique nonlinear vertex to replace all the virtual endmembers. Unlike the virtual endmembers, this vertex actually works as an additional true endmember that gives affine representations of pixels with other true endmembers. When the pixels’ normalized barycentric coordinates with respect to true endmembers are obtained, they will be directly projected to be their approximate linear mixture components, which removes the collinearity effectively and enables further linear spectral unmixing. After that, based on the analysis of projection bias, two strategies using the projected gradient algorithm and a traditional linear spectral unmixing algorithm, respectively, are provided to correct the bias and estimate more accurate abundances. The experimental results on simulated and real hyperspectral data show that the proposed algorithm performs better compared with both traditional and state-of-the-art spectral unmixing algorithms. Both the unmixing accuracy and speed have been improved.
Autors: Bin Yang;Bin Wang;Zongmin Wu;
Appeared in: IEEE Transactions on Geoscience and Remote Sensing
Publication date: Feb 2018, volume: 56, issue:2, pages: 694 - 714
Publisher: IEEE
 
» Not All Negatives Are Equal: Learning to Track With Multiple Background Clusters
Abstract:
Conventional tracking-by-detection approaches for visual object tracking often assume that the task at hand is a binary foreground-versus-background classification problem, in which the background is a single, generic, and all-inclusive class. In contrast, here we argue that the background appearance, for the most part, possesses a more complicated structure that would benefit from further partitioning into multiple contextual clusters. Our observation is that, although the background class is contemplated to contain a vast intra-class variation, during the tracking process, only a small portion of this diversity is present at the current frame around the foreground object. This observation motivates us to build multiple fine-grained foreground-versus-contextual-cluster models that provide more discriminative classifications, and consequently more robust and accurate foreground object tracking. For each cluster, we employ a structured output support vector machine (SSVM), and in an online manner, we combine the responses of multiple classifiers. To this end, we apply a top-level SSVM that models the tracked foreground object. We show that our refined modeling of the background is better than naïvely growing the complexity of a single foreground–background classifier, i.e., increasing the number of support vectors that existing approaches rely on, which cause overfitting issues. Our extensive evaluations on large benchmark data sets demonstrate that our tracker consistently outperforms the current state-of-the-art while having comparable computational requirements.
Autors: Gao Zhu;Fatih Porikli;Hongdong Li;
Appeared in: IEEE Transactions on Circuits and Systems for Video Technology
Publication date: Feb 2018, volume: 28, issue:2, pages: 314 - 326
Publisher: IEEE
 
» Not your Father's analog computer
Abstract:
WHEN NEIL ARMSTRONG and Buzz Aldrin landed on the moon in 1969 as part of the Apollo 11 mission, it was perhaps the greatest achievement in the history of engineering. Many people don't realize, though, that an important ingredient in the success of the Apollo missions and their predecessors were analog and hybrid (analog- digital) computers, which NASA used for simulations and in some cases even flight control. Indeed, many people today have never even heard of analog computers, believing that a computer is, by definition, a digital device.
Autors: Yannis Tsividis;
Appeared in: IEEE Spectrum
Publication date: Feb 2018, volume: 55, issue:2, pages: 38 - 43
Publisher: IEEE
 
» Novel Addressable Test Structure for Detecting Soft Failure of Resistive Elements When Developing Manufacturing Procedures
Abstract:
A novel addressable test structure for detecting soft failures of resistive elements is proposed. Its architecture is much simpler than that of previous works, but all functions needed to analyze the electrical properties of detected failures, for example, the aging test with overcurrent, can be realized within the architecture. This makes it more powerful than previous designs. Since the addressable test structure proposed here also has a smaller footprint, it can realize cost effective evaluations.
Autors: Shingo Sato;Yasuhisa Omura;
Appeared in: IEEE Transactions on Semiconductor Manufacturing
Publication date: Feb 2018, volume: 31, issue:1, pages: 124 - 129
Publisher: IEEE
 
» Novel Design Space of Load Modulated Continuous Class-B/J Power Amplifier
Abstract:
A novel design space of load modulated (LM) continuous Class-B/J power amplifiers (PAs) is proposed, and a detailed mathematical analysis is presented. The combination of LM technique and continuous mode is introduced to enhance the wideband performance of LM PAs. An inversely proportional relationship between and is derived, which indicates that the nonlinear can affect the optimal load impedances at output power backoff (OPBO) and the design parameter should be appropriately adjusted. The measured results of a PA prototype show that the PAE is 39%–45% under LM when OPBO = 5 dB across 1.6–2.4 GHz. Compared with the same PA with fixed , the proposed PA with optimum at 2 GHz achieves a PAE improvement with 11% when OPBO = 5 dB.
Autors: Xuekun Du;Chang Jiang You;Jingye Cai;Mohamed Helaoui;Fadhel M. Ghannouchi;Yulong Zhao;Xiang Li;
Appeared in: IEEE Microwave and Wireless Components Letters
Publication date: Feb 2018, volume: 28, issue:2, pages: 156 - 158
Publisher: IEEE
 
» Novel Dynamic State-Deflection Method for Gate-Level Design Obfuscation
Abstract:
The emerging security threats in the integrated circuit supply chain do not only challenge the chip integrity, but also raise serious concerns on hardware intellectual property (IP) piracy. Hardware design obfuscation is a promising countermeasure to resist reverse engineering attacks and IP piracy. The majority of existing hardware obfuscation methods modify the original finite state machine (FSM) by adding additional state transitions and utilizing a key sequence to lock the transition from the nonfunctional states to the functional reset state. Those methods are effective to prevent attackers from entering the normal functional mode but they lack resilience if the FSM is already in the normal mode. This paper proposes to protect all the states with a low-cost state-deflection-based obfuscation method, which dynamically deflects state transitions from the original transition path to a black hole cluster if a wrong key is applied. Unlike other works that use static transitions between legal states to black hole states at the design time, this method utilizes a state rotation function (Rotatefunc) and selective register flipping function (Mapfunc) to dynamically control the state deflection paths. Hence, the difficulty of reverse engineering and thwarting register overwrite attacks is increased. Simulations performed on ISCAS’89 benchmark circuits show that the proposed method significantly reduces the difference of the net toggle activities between the correct and wrong key scenarios, and achieves up to 56% higher code coverage than the most efficient obfuscation method. Thanks to the dynamic deflection feature, on average, this method generates about 100 more unique state register patterns than other methods with moderate power increase. Moreover, the proposed method achieves the Hamming distance of primary outputs and state registers close to 50%.
Autors: Jaya Dofe;Qiaoyan Yu;
Appeared in: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Publication date: Feb 2018, volume: 37, issue:2, pages: 273 - 285
Publisher: IEEE
 
» Novel High-Performance Bondwire Chip-to-Chip Interconnections for Applications Up to 220 GHz
Abstract:
This letter presents a novel chip-to-chip interconnect technology for millimeter-wave and ultra-wideband applications. The technique relies on magnetic coupling between half-loop bondwires to transfer power over pads of semiconductor dies provided with crack stops. Conventional aluminum wires with a diameter of are used to fabricate a set of low-cost half-loops, investigating the performance of the interface. The technique demonstrated minimum insertion loss of 1.9 dB over frequency bands wider than 40 GHz located in the band 140–220 GHz. Agreement with simulations is also shown. To the best of the author’s knowledge, the presented solution is the first bondwire chip-to-chip interconnections for ultra-wideband operations up to 220 GHz and suitable to chips provided with crack stops.
Autors: Paolo Valerio Testa;Corrado Carta;Frank Ellinger;
Appeared in: IEEE Microwave and Wireless Components Letters
Publication date: Feb 2018, volume: 28, issue:2, pages: 102 - 104
Publisher: IEEE
 
» Novel Quantitative Analytical Approaches for Rotor Identification and Associated Implications for Mapping
Abstract:
Goal: Clinical studies identifying rotors and confirming these sites for ablation in treating cardiac arrhythmias have had inconsistent results with the currently available analysis techniques. The aim of this study is to evaluate four new signal analysis approaches—multiscale frequency (MSF), Shannon entropy (SE), Kurtosis (Kt), and multiscale entropy (MSE)—in their ability to identify the pivot point of rotors. Methods: Optical mapping movies of ventricular tachycardia were used to evaluate the performance and robustness of SE, Kt, MSF, and MSE techniques with respect to several clinical limitations: decreased time duration, reduced spatial resolution, and the presence of meandering rotors. To quantitatively assess the robustness of the four techniques, results were compared to the “true” rotor(s) identified using optical mapping-based phase maps. Results: The results demonstrate that MSF, Kt, and MSE accurately identified both stationary and meandering rotors. In addition, these techniques remained accurate under simulated clinical limitations: shortened electrogram duration and decreased spatial resolution. Artifacts mildly affected the performance of MSF, Kt, and MSE, but strongly impacted the performance of SE. Conclusion: These results motivate further validation using intracardiac electrograms to see if these approaches can map rotors in a clinical setting and whether they apply to more complex arrhythmias including atrial or ventricular fibrillation. Significance: New techniques providing more accurate rotor localization could improve characterization of arrhythmias and, in turn, offer a means to accurately evaluate whether rotor ablation is a viable and effective treatment for chaotic cardiac arrhythmias.
Autors: Elizabeth M. Annoni;Shivaram Poigai Arunachalam;Suraj Kapa;Siva K. Mulpuru;Paul A. Friedman;Elena G. Tolkacheva;
Appeared in: IEEE Transactions on Biomedical Engineering
Publication date: Feb 2018, volume: 65, issue:2, pages: 273 - 281
Publisher: IEEE
 
» Novel Radar Techniques and Applications [Book Review]
Abstract:
Autors: Hao Ling;
Appeared in: IEEE Antennas and Propagation Magazine
Publication date: Feb 2018, volume: 60, issue:1, pages: 132 - 134
Publisher: IEEE
 
» Novel Single-Source Surface Integral Equation for Scattering Problems by 3-D Dielectric Objects
Abstract:
A new single-source integral equation is proposed for the solution of electromagnetic wave scattering problems. The traditional volume electric field integral equation is reduced to the new single-source surface integral equation by representing the electric field inside the scatterer as a superposition of spherical waves emanating from its boundary. Such new integral equation formulation has been previously developed for the scalar and vector cases of 2-D scattering problems. In this paper, the 3-D form of this new single-source surface integral equation for scattering on homogeneous nonmagnetic dielectrics is proposed. Detailed description of the method of moments (MoMs) discretization and its resultant matrices is presented. In order to validate the new integral equation formulation and verify the accuracy of its MoMs discretization, its solution is compared against the analytical Mie series solution and fields computed using the commercial electromagnetic analysis software.
Autors: Farhad Sheikh Hosseini Lori;Anton Menshov;Reza Gholami;Jamiu Babatunde Mojolagbe;Vladimir I. Okhmatovski;
Appeared in: IEEE Transactions on Antennas and Propagation
Publication date: Feb 2018, volume: 66, issue:2, pages: 797 - 807
Publisher: IEEE
 
» Numerical Model Reduction for the Prediction of Interface Pressure Applied by Compression Bandages on the Lower Leg
Abstract:
Objective: To develop a new method for the prediction of interface pressure applied by medical compression bandages. Methods: A finite element simulation of bandage application was designed, based on patient-specific leg geometries. For personalized interface pressure prediction, a model reduction approach was proposed, which included the parametrization of the leg geometry. Pressure values computed with this reduced model were then confronted to experimental pressure values. Results: The most influencing parameters were found to be the bandage tension, the skin-to-bandage friction coefficient and the leg morphology. Thanks to the model reduction approach, it was possible to compute interface pressure as a linear combination of these parameters. The pressures computed with this reduced model were in agreement with experimental pressure values measured on 66 patients’ legs. Conclusion: This methodology helps to predict patient-specific interface pressure applied by compression bandages within a few minutes whereas it would take a few days for the numerical simulation. The results of this method show less bias than Laplace's Law, which is for now the only other method for interface pressure computation.
Autors: Fanette Chassagne;Jérôme Molimard;Reynald Convert;Pascal Giraux;Pierre Badel;
Appeared in: IEEE Transactions on Biomedical Engineering
Publication date: Feb 2018, volume: 65, issue:2, pages: 449 - 457
Publisher: IEEE
 
» Numerical Simulation and Field Test of the Transient Temperature Rise of HVdc Grounding Electrodes
Abstract:
This paper investigates the temperature rise of vertical/horizontal high-voltage direct current (HVdc) grounding electrodes by simulations and field tests. Based on a field-circuit coupling current distribution model and a three dimensional (3-D) finite element model, a comprehensive methodology is proposed to analyze the transient temperature rise. Since soil resistivity varies with temperature around the electrodes, the temperature-dependent soil resistivity is tested, and then approximated by an empirical formula. Moreover, two practical tests are implemented to validate the simulation model. By ignoring the underground water fluctuations, the calculation results match test results nicely, which demonstrates that the terminal effect of the vertical electrode significantly affects the temperature distribution. But for a horizontal grounding electrode, the current distribution is more uniform than the vertical one. This study provides valuable references for design of HVdc grounding electrodes.
Autors: Yu Wang;Zhuohong Pan;Zhipeng Zha;Bo Tan;Xishan Wen;Yu Liu;Jingzhuo Zhang;Lei Lan;
Appeared in: IEEE Transactions on Power Delivery
Publication date: Feb 2018, volume: 33, issue:1, pages: 22 - 31
Publisher: IEEE
 
» Obituary for Lotfi A. Zadeh [In Memoriam]
Abstract:
Recounts the career and contributions of Lotfi A. Zadeh.
Autors: Piero P. Bonissone;
Appeared in: IEEE Computational Intelligence Magazine
Publication date: Feb 2018, volume: 13, issue:1, pages: 13 - 22
Publisher: IEEE
 
» Object Tracking in Satellite Videos by Fusing the Kernel Correlation Filter and the Three-Frame-Difference Algorithm
Abstract:
Object tracking is a popular topic in the field of computer vision. The detailed spatial information provided by a very high resolution remote sensing sensor makes it possible to track targets of interest in satellite videos. In recent years, correlation filters have yielded promising results. However, in terms of dealing with object tracking in satellite videos, the kernel correlation filter (KCF) tracker achieves poor results due to the fact that the size of each target is too small compared with the entire image, and the target and the background are very similar. Therefore, in this letter, we propose a new object tracking method for satellite videos by fusing the KCF tracker and a three-frame-difference algorithm. A specific strategy is proposed herein for taking advantage of the KCF tracker and the three-frame-difference algorithm to build a strong tracker. We evaluate the proposed method in three satellite videos and show its superiority to other state-of-the-art tracking methods.
Autors: Bo Du;Yujia Sun;Shihan Cai;Chen Wu;Qian Du;
Appeared in: IEEE Geoscience and Remote Sensing Letters
Publication date: Feb 2018, volume: 15, issue:2, pages: 168 - 172
Publisher: IEEE
 
» On Coding for Endurance Enhancement and Error Control of Phase Change Memories With Write Latency Reduction
Abstract:
This paper addresses at coding-level the challenge of providing a write latency reduction with either endurance enhancement and/or error control for a phase change memory (PCM) system. Endurance enhancement is assessed by considering the skewed write operations among the cells of a PCM system, i.e., when the maximal number of cell write operations is smaller, then the coding scheme achieves a better endurance, because the access of the memory cells in the system is more uniform (less skewed). As a first contribution, simulation of different industrial benchmarks shows that for realistic code rates (such as at / = 4/5), the write time speed-up (WTS) code not only reduces the write latency as previously reported, but it also reduces the skewed (nonuniform) use of PCM cells. This occurs because the WTS code uses as many cells as possible to reduce the number of SET operations in a PCM cell. Then, error control is considered. An encoding/decoding scheme that is compatible with a write latency reduction code, such as WTS, is proposed. For compatibility with the write latency reduction, a partition-based error control code (ECC) must be used. Also, the ECCs employed in these cases are systematic. The original information always appears in the codeword without modification. Evaluation by simulation shows that also in this case, the maximal number of write operations of the WTS code is smaller.
Autors: Kazuteru Namba;Fabrizio Lombardi;
Appeared in: IEEE Transactions on Very Large Scale Integration Systems
Publication date: Feb 2018, volume: 26, issue:2, pages: 230 - 238
Publisher: IEEE
 
» On Constructions of Reed-Muller Subcodes
Abstract:
In this letter, subcodes constructed from Reed–Muller codes by removal of generator matrix rows are considered. A new greedy algorithm based on the overlap of generator matrix rows is developed. To select the best subcode generated by the greedy algorithm, the number of minimum weight code words is determined. Computer simulations confirm that the greedy algorithm outperforms the three other construction methods, generating the best codes among all presented subcodes.
Autors: Johannes Van Wonterghem;Joseph J. Boutros;Marc Moeneclaey;
Appeared in: IEEE Communications Letters
Publication date: Feb 2018, volume: 22, issue:2, pages: 220 - 223
Publisher: IEEE
 
» On DC Fault Dynamics of MMC-Based HVdc Connections
Abstract:
This paper studies the dc fault development stages and analyzes the fault dynamics in a point-to-point multilevel modular converters (MMC)-based dc connection. First, the effect of the dc grid configuration on the normal operation was investigated by comparing an asymmetric monopole with metallic return and a symmetric monopole. Then, the main parameters that affect the dc fault response of a grid, such as the fault type, impedance and converter blocking, were examined. Compared to previous studies, which are based on simulation results, the analysis is performed hereby both in theory, deriving the equations that describe the dc fault stages, as well as using experimental results obtained in the designed laboratory setup. The setup consists of two MMC terminals connected to two ac sources representing independent ac grids. These terminals are connected using a simple dc link based on pi-section equivalent of dc cables. The obtained results, which verified the theoretical analysis, can be used to determine the protection function thresholds of the MMC, as well as to estimate the developed stresses on dc lines during fault conditions and to define the design requirements for dc breakers.
Autors: Epameinondas Kontos;Georgios Tsolaridis;Remus Teodorescu;Pavol Bauer;
Appeared in: IEEE Transactions on Power Delivery
Publication date: Feb 2018, volume: 33, issue:1, pages: 497 - 507
Publisher: IEEE
 
» On Decoding Rank-Metric Codes Over Large Fields
Abstract:
A decoding algorithm is presented for a rank-metric array codes that are based on diagonal interleaving of maximum-distance separable codes. With respect to this metric, such array codes are known to be optimal when the underlying field is algebraically closed. It is also shown that for any list decoding radius that is smaller than the minimum rank distance, the list size can be bounded from above by an expression that is independent of the field.
Autors: Ron M. Roth;
Appeared in: IEEE Transactions on Information Theory
Publication date: Feb 2018, volume: 64, issue:2, pages: 944 - 951
Publisher: IEEE
 
» On Demand Spatial Beam Self-Focusing in Hexagonal Multicore Fiber
Abstract:
Combination of the classical effect of light self-focusing and recently emerged multicore fiber technology offers new opportunities for the spatio-temporal control and manipulation of high-power light radiation. Here, we apply genetic algorithm to design a system enabling self-focusing of light in various fiber cores on demand. The proposed concept is general and can be applied and adapted to any multicore fiber or two-dimensional array of coupled waveguides paving a way for numerous applications.
Autors: Igor S. Chekhovskoy;Mariia A. Sorokina;Alexander M. Rubenchik;Mikhail P. Fedoruk;Sergei K. Turitsyn;
Appeared in: IEEE Photonics Journal
Publication date: Feb 2018, volume: 10, issue:1, pages: 1 - 8
Publisher: IEEE
 
» On Distributed Fuzzy Decision Trees for Big Data
Abstract:
Fuzzy decision trees (FDTs) have shown to be an effective solution in the framework of fuzzy classification. The approaches proposed so far to FDT learning, however, have generally neglected time and space requirements. In this paper, we propose a distributed FDT learning scheme shaped according to the MapReduce programming model for generating both binary and multiway FDTs from big data. The scheme relies on a novel distributed fuzzy discretizer that generates a strong fuzzy partition for each continuous attribute based on fuzzy information entropy. The fuzzy partitions are, therefore, used as an input to the FDT learning algorithm, which employs fuzzy information gain for selecting the attributes at the decision nodes. We have implemented the FDT learning scheme on the Apache Spark framework. We have used ten real-world publicly available big datasets for evaluating the behavior of the scheme along three dimensions: 1) performance in terms of classification accuracy, model complexity, and execution time; 2) scalability varying the number of computing units; and 3) ability to efficiently accommodate an increasing dataset size. We have demonstrated that the proposed scheme turns out to be suitable for managing big datasets even with a modest commodity hardware support. Finally, we have used the distributed decision tree learning algorithm implemented in the MLLib library and the Chi-FRBCS-BigData algorithm, a MapReduce distributed fuzzy rule-based classification system, for comparative analysis.
Autors: Armando Segatori;Francesco Marcelloni;Witold Pedrycz;
Appeared in: IEEE Transactions on Fuzzy Systems
Publication date: Feb 2018, volume: 26, issue:1, pages: 174 - 192
Publisher: IEEE
 
» On Effectiveness of Transfer Learning Approach for Neural Network-Based Virtual Metrology Modeling
Abstract:
Virtual metrology (VM) technologies have been successfully developed to enable wafer-to-wafer quality monitoring with reduced costs in the semiconductor manufacturing process. VM estimates an inspection task by predicting metrology variables as a function of process variables using prediction models trained with previous wafer records collected from the involved set of equipment. However, it is difficult to obtain accurate prediction models, in particular for a newly adopted equipment set, if the number of wafer records for the target equipment set are insufficient. While collecting more records is time-consuming and costly, the abundant data of related equipment sets are fruitful sources to improve VM modeling for an equipment set. Here, we investigate the effectiveness of a transfer learning approach based on neural networks to circumvent data insufficiency. This approach exploits knowledge acquired from previously established VM models of other equipment sets to improve the VM modeling on the target equipment set. Experimental results of the implementation with neural networks on actual datasets demonstrate its superiority in both aspects of metrology accuracy and computational efficiency compared with a traditional independent learning approach.
Autors: Seokho Kang;
Appeared in: IEEE Transactions on Semiconductor Manufacturing
Publication date: Feb 2018, volume: 31, issue:1, pages: 149 - 155
Publisher: IEEE
 
» On Properties of the Support of Capacity-Achieving Distributions for Additive Noise Channel Models With Input Cost Constraints
Abstract:
We study the classical problem of characterizing the channel capacity and its achieving distribution in a generic fashion. We derive a simple relation between three parameters: the input–output function, the input cost function, and the noise probability density function, one which dictates the type of the optimal input. In layman terms, we prove that the support of the optimal input is bounded whenever the cost grows faster than a “cutoff” growth rate equal to the logarithm of the inverse of the noise probability density function evaluated at the input–output function. Furthermore, we prove a converse statement that says whenever the cost grows slower than the “cutoff” rate, the optimal input has necessarily an unbounded support. In addition, we show how the discreteness of the optimal input is guaranteed whenever the triplet satisfy some analyticity properties. We argue that a suitable cost function to be imposed on the channel input is one that grows similarly to the “cutoff” rate. Our results are valid for any cost function that is super-logarithmic. They summarize a large number of previous channel capacity results and give new ones for a wide range of communication channel models, such as Gaussian mixtures, generalized-Gaussians, and heavy-tailed noise models, that we state along with numerical computations.
Autors: Jihad Fahs;Ibrahim Abou-Faycal;
Appeared in: IEEE Transactions on Information Theory
Publication date: Feb 2018, volume: 64, issue:2, pages: 1178 - 1198
Publisher: IEEE
 
» On Protocol and Physical Interference Models in Poisson Wireless Networks
Abstract:
This paper analyzes the connection between the protocol and physical interference models in the setting of Poisson wireless networks. A transmission is successful under the protocol model if there are no interferers within a parameterized guard zone around the receiver, while a transmission is successful under the physical model if the signal to interference plus noise ratio at the receiver is above a threshold. The parameterized protocol model forms a family of decision rules for predicting the success or failure of the same transmission attempt under the physical model. For Poisson wireless networks, we employ stochastic geometry to determine the prior, evidence, and posterior distributions associated with this estimation problem. With this in hand, we proceed to develop six sets of results: 1) the maximum correlation of protocol and physical model success indicators; 2) the minimum Bayes risk in estimating physical success from a protocol observation; 3) the receiver operating characteristic (ROC) of false rejection (Type I) and false acceptance (Type II) probabilities; 4) the impact of Rayleigh fading versus no fading on the correlation and ROC; 5) the impact of multiple prior protocol model observations in the setting of a wireless network with a fixed set of nodes in which the nodes employ the slotted Aloha protocol in each time slot; and 6) a numerical investigation of the effect of different pathloss models.
Autors: Jeffrey Wildman;Steven Weber;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Feb 2018, volume: 17, issue:2, pages: 808 - 821
Publisher: IEEE
 
» On Some Input–Output Dynamic Properties of Complex Networks
Abstract:
In this brief, we obtain the relationship between dynamic properties of system and network structures of complex networks. We show that the sum of the product of weights of the shortest paths between control and output nodes is equal to the gain factor of the pole-zero-gain transfer function of the complex network. We also show that dc-gain for the peripheral nodes of the complex network depends on the distance between the control and output nodes in the network. Existence of non-minimum phase zeros for collocated control and output nodes is discussed. The theoretical developments are verified using IEEE-4 bus power networked system application.
Autors: Ram Niwash Mahia;Deepak M. Fulwani;
Appeared in: IEEE Transactions on Circuits and Systems II: Express Briefs
Publication date: Feb 2018, volume: 65, issue:2, pages: 216 - 220
Publisher: IEEE
 
» On the Algorithmization of Janashia-Lagvilava Matrix Spectral Factorization Method
Abstract:
We consider three different ways of algorithmization of the Janashia–Lagvilava spectral factorization method. The first algorithm is faster than the second one, however, it is only suitable for matrices of low dimension. The second algorithm, on the other hand, can be applied to matrices of substantially larger dimension. The third algorithm is a superfast implementation of the method, but only works in the polynomial case under the additional restriction that the zeros of the determinant are not too close to the boundary. All three algorithms fully utilize the advantage of the method, which carries out spectral factorization of leading principal submatrices step-by-step. The corresponding results of numerical simulations are reported in order to describe the characteristic features of each algorithm and compare them to other existing algorithms.
Autors: Lasha Ephremidze;Faisal Saied;Ilya Matvey Spitkovsky;
Appeared in: IEEE Transactions on Information Theory
Publication date: Feb 2018, volume: 64, issue:2, pages: 728 - 737
Publisher: IEEE
 
» On the Convergence of the Sparse Possibilistic C-Means Algorithm
Abstract:
In this paper, a convergence proof for the recently proposed cost function optimization sparse possibilistic c-means (SPCM) algorithm is provided. Specifically, it is shown that the algorithm will converge to one of the local minima of its associated cost function. It is also shown that similar convergence results can be derived for the well-known possibilistic c-means (PCM) algorithm proposed by Krishnapuram and Keller, 1996, if we view it as a special case of SPCM. Note that the convergence results for PCM are stronger than those established in previous works.
Autors: Konstantinos D. Koutroumbas;Spyridoula D. Xenaki;Athanasios A. Rontogiannis;
Appeared in: IEEE Transactions on Fuzzy Systems
Publication date: Feb 2018, volume: 26, issue:1, pages: 324 - 337
Publisher: IEEE
 
» On the Differential Input Impedance of an Electro-Explosive Device
Abstract:
In this paper, a model for the input impedance of a hot-wire electro-explosive device (EED) based on differential-mode measurements is proposed. The model represents the EED using three transmission line segments in cascade. The characteristics of each segment are estimated according to data reported in the literature and to measurements of the differential-mode input impedance of actual EEDs in the ultrahigh frequency range. The experimental procedure and model are presented in detail. In addition, the impedance measurements and the predictions of the proposed model are compared with previous results reported in the literature.
Autors: John J. Pantoja;Felix Vega;Francisco Román;Nestor Peña;Farhad Rachidi;
Appeared in: IEEE Transactions on Microwave Theory and Techniques
Publication date: Feb 2018, volume: 66, issue:2, pages: 858 - 864
Publisher: IEEE
 
» On the Discrete Bisymmetry
Abstract:
It is known that bisymmetry generalizes the simultaneous commutativity and associativity in the framework of the unit interval. In this work, we will completely characterize two classes of bisymmetric aggregation operators: one with a neutral element and the other with the vertical and horizontal sections of the idempotent elements being smooth on a finite chain, but not necessarily smooth and commutative. Thus, the previous results, based on the smoothness that is known as a very restrictive condition, are improved. For example, there is only one smooth Archimedean t-norm on a finite chain. In this paper, the discrete bisymmetric aggregation operators are explored without the limit of the smoothness. As a by-product, it is deduced that for smooth aggregation operators on a finite chain, the bisymmetry is equivalent to the commutativity and associativity, which improves the conclusion obtained by Mas et al. that associativity and bisymmetry are equivalent for commutative smooth aggregation operators on a finite chain.
Autors: Yong Su;Hua-Wen Liu;Witold Pedrycz;
Appeared in: IEEE Transactions on Fuzzy Systems
Publication date: Feb 2018, volume: 26, issue:1, pages: 374 - 378
Publisher: IEEE
 
» On the Discreteness of Capacity-Achieving Distributions for Fading and Signal-Dependent Noise Channels With Amplitude-Limited Inputs
Abstract:
We address the problem of finding the capacity of two classes of channels with amplitude-limited inputs. The first class is frequency flat fading channels with an arbitrary (but finite support) channel gain with the channel state information available only at the receiver side; while the second one we consider is the class of additive noise channels with signal-dependent Gaussian noise. We show that for both channel models and under some regularity conditions, the capacity-achieving distribution is discrete with a finite number of mass points. Furthermore, finding the capacity-achieving distribution turns out to be a finite-dimensional optimization problem, and efficient numerical algorithms can be developed using standard optimization techniques to compute the channel capacity. We demonstrate our findings via several examples. In particular, we present an example for a block fading channel where the channel gain follows a truncated Rayleigh distribution, and two instances of signal-dependent noise that are used in the literature of magnetic recording and optical communication channels.
Autors: Ahmad Elmoslimany;Tolga M. Duman;
Appeared in: IEEE Transactions on Information Theory
Publication date: Feb 2018, volume: 64, issue:2, pages: 1163 - 1177
Publisher: IEEE
 
» On the Fast and Precise Evaluation of the Outage Probability of Diversity Receivers Over $alpha -mu $ , $kappa -mu $ , and $eta -mu $ Fading Channels
Abstract:
In this paper, we are interested in determining the cumulative distribution function of the sum of , , and random variables in the setting of rare event simulations. To this end, we present a simple and efficient importance sampling approach. The main result of this work is the bounded relative error property of the proposed estimators. Capitalizing on this result, we accurately estimate the outage probability of multibranch maximum ratio combining and equal gain diversity receivers over , , and fading channels. Selected numerical simulations are discussed to show the robustness of our estimators compared with naive Monte Carlo estimators.
Autors: Chaouki Ben Issaid;Mohamed-Slim Alouini;Raul Tempone;
Appeared in: IEEE Transactions on Wireless Communications
Publication date: Feb 2018, volume: 17, issue:2, pages: 1255 - 1268
Publisher: IEEE
 
» On the Geometric Ergodicity of Metropolis-Hastings Algorithms for Lattice Gaussian Sampling
Abstract:
Sampling from the lattice Gaussian distribution has emerged as an important problem in coding, decoding, and cryptography. In this paper, the classic Metropolis-Hastings (MH) algorithm in Markov chain Monte Carlo methods is adopted for lattice Gaussian sampling. Two MH-based algorithms are proposed, which overcome the limitation of Klein’s algorithm. The first one, referred to as the independent Metropolis-Hastings-Klein (MHK) algorithm, establishes a Markov chain via an independent proposal distribution. We show that the Markov chain arising from this independent MHK algorithm is uniformly ergodic, namely, it converges to the stationary distribution exponentially fast regardless of the initial state. Moreover, the rate of convergence is analyzed in terms of the theta series, leading to predictable mixing time. A symmetric Metropolis-Klein algorithm is also proposed, which is proven to be geometrically ergodic.
Autors: Zheng Wang;Cong Ling;
Appeared in: IEEE Transactions on Information Theory
Publication date: Feb 2018, volume: 64, issue:2, pages: 738 - 751
Publisher: IEEE
 
» On the Minimum Output Entropy of Random Orthogonal Quantum Channels
Abstract:
We consider the sequences of random quantum channels defined by using the Stinespring formula with Haar-distributed random orthogonal matrices. For any fixed sequence of input states, we study the asymptotic eigenvalue distribution of the outputs through the tensor powers of random channels. We show that the input states achieving minimum output entropy are tensor products of maximally entangled states (Bell states) when the tensor power is even. This phenomenon is completely different from the one for random quantum channels constructed from Haar-distributed random unitary matrices, which leads us to formulate some conjectures about the regularized minimum output entropy.
Autors: Motohisa Fukuda;Ion Nechita;
Appeared in: IEEE Transactions on Information Theory
Publication date: Feb 2018, volume: 64, issue:2, pages: 1374 - 1384
Publisher: IEEE
 
» On the Performance of MIMO-NOMA-Based Visible Light Communication Systems
Abstract:
In this letter, we apply the non-orthogonal multiple access (NOMA) technique to improve the achievable sum rate of multiple-input multiple-output (MIMO)-based multi-user visible light communication (VLC) systems. To ensure efficient and low-complexity power allocation in indoor MIMO-NOMA-based VLC systems, a normalized gain difference power allocation (NGDPA) method is first proposed by exploiting users’ channel conditions. We investigate the performance of an indoor MIMO-NOMA-based multi-user VLC system through numerical simulations. The obtained results show that the achievable sum rate of the MIMO-VLC system can be significantly improved by employing NOMA with the proposed NGDPA method. It is demonstrated that NOMA with NGDPA achieves a sum rate improvement of up to 29.1% compared with NOMA with the gain ratio power allocation method in the MIMO-VLC system with three users.
Autors: Chen Chen;Wen-De Zhong;Helin Yang;Pengfei Du;
Appeared in: IEEE Photonics Technology Letters
Publication date: Feb 2018, volume: 30, issue:4, pages: 307 - 310
Publisher: IEEE
 
» On the Price of Proactivizing Round-Optimal Perfectly Secret Message Transmission
Abstract:
In a network of n nodes (modelled as a digraph), the goal of a perfectly secret message transmission (PSMT) protocol is to replicate sender’s message m at the receiver’s end without revealing any information about m to a computationally unbounded adversary that eavesdrops on any t nodes. The adversary may be mobile too – that is, it may eavesdrop on a different set of t nodes in different rounds. We prove a necessary and sufficient condition on the synchronous network for the existence of r-round PSMT protocols, for any given r > 0; further, we show that round-optimality is achieved without trading-off the communication complexity; specifically, our protocols have an overall communication complexity of O(n) elements of a finite field to perfectly transmit one field element. Apart from optimality/scalability, two interesting implications of our results are: (a) adversarial mobility does not affect its tolerability: PSMT tolerating a static t-adversary is possible if and only if PSMT tolerating mobile t-adversary is possible; and (b) mobility does not affect the round optimality: the fastest PSMT protocol tolerating a static t-adversary is not faster than the one tolerating a mobile t-adversary.
Autors: Ravi Kishore;Ashutosh Kumar;Chiranjeevi Vanarasa;Kannan Srinathan;
Appeared in: IEEE Transactions on Information Theory
Publication date: Feb 2018, volume: 64, issue:2, pages: 1404 - 1422
Publisher: IEEE
 
» On the Reliability of Individual Brain Activity Networks
Abstract:
There is intense interest in fMRI research on whole-brain functional connectivity, and however, two fundamental issues are still unresolved: the impact of spatiotemporal data resolution (spatial parcellation and temporal sampling) and the impact of the network construction method on the reliability of functional brain networks. In particular, the impact of spatiotemporal data resolution on the resulting connectivity findings has not been sufficiently investigated. In fact, a number of studies have already observed that functional networks often give different conclusions across different parcellation scales. If the interpretations from functional networks are inconsistent across spatiotemporal scales, then the whole validity of the functional network paradigm is called into question. This paper investigates the consistency of resting state network structure when using different temporal sampling or spatial parcellation, or different methods for constructing the networks. To pursue this, we develop a novel network comparison framework based on persistent homology from a topological data analysis. We use the new network comparison tools to characterize the spatial and temporal scales under which consistent functional networks can be constructed. The methods are illustrated on Human Connectome Project data, showing that the DISCOH2 network construction method outperforms other approaches at most data spatiotemporal resolutions.
Autors: Ben Cassidy;F. DuBois Bowman;Caroline Rae;Victor Solo;
Appeared in: IEEE Transactions on Medical Imaging
Publication date: Feb 2018, volume: 37, issue:2, pages: 649 - 662
Publisher: IEEE
 
» On the Remarkable Performance of the Series-Resonance CMOS Oscillator
Abstract:
Common harmonic oscillator topologies, such as class-B and class-C, are typically unable to meet ultra stringent phase noise requirements, due to the exceedingly large capacitance (and, symmetrically, low inductance) that would be required in the parallel resonator. In this paper, we show that an oscillator making use of series resonators is ideally able to overcome this limitation, with the additional, surprising benefit that the phase noise contribution from the active oscillator core can be made negligible, provided that very good MOS switches are available.
Autors: Federico Pepe;Andrea Bevilacqua;Pietro Andreani;
Appeared in: IEEE Transactions on Circuits and Systems I: Regular Papers
Publication date: Feb 2018, volume: 65, issue:2, pages: 531 - 542
Publisher: IEEE
 
» On the Stability of Fast Retrial Multichannel ALOHA With Rate Control for MTC
Abstract:
We consider multichannel ALOHA for machine-type communications to support a number of devices with multiple subchannels in this letter. In particular, we focus on the stability of multichannel ALOHA when only fast retrial is employed for re-transmissions of collided packets. For the stability analysis, the Foster–Lyapunov criterion is considered. For a stable system, the rate control is applied, and a certain rate control scheme of limited feedback is proposed.
Autors: Jinho Choi;
Appeared in: IEEE Communications Letters
Publication date: Feb 2018, volume: 22, issue:2, pages: 360 - 363
Publisher: IEEE
 
» On the Techniques to Develop Millimeter-Wave Textile Integrated Waveguides Using Rigid Warp Threads
Abstract:
Two millimeter-wave textile integrated wave- guides (TIWs), which only differ in the employed substrate, have been designed, manufactured, and experimentally characterized. Both waveguides are based on the conventional substrate integrated waveguide technology while being fully integrated in textile. The manufactured prototypes have been characterized by using a back to back TIW to rectangular waveguide transition. The theoretically predicted behavior of the prototypes has been experimentally verified.
Autors: Leticia Alonso-González;Samuel Ver-Hoeye;Carlos Vázquez-Antuña;Miguel Fernández-García;Fernando Las-Heras Andrés;
Appeared in: IEEE Transactions on Microwave Theory and Techniques
Publication date: Feb 2018, volume: 66, issue:2, pages: 751 - 761
Publisher: IEEE
 
» On-Chip Neural Data Compression Based On Compressed Sensing With Sparse Sensing Matrices
Abstract:
On-chip neural data compression is an enabling technique for wireless neural interfaces that suffer from insufficient bandwidth and power budgets to transmit the raw data. The data compression algorithm and its implementation should be power and area efficient and functionally reliable over different datasets. Compressed sensing is an emerging technique that has been applied to compress various neurophysiological data. However, the state-of-the-art compressed sensing (CS) encoders leverage random but dense binary measurement matrices, which incur substantial implementation costs on both power and area that could offset the benefits from the reduced wireless data rate. In this paper, we propose two CS encoder designs based on sparse measurement matrices that could lead to efficient hardware implementation. Specifically, two different approaches for the construction of sparse measurement matrices, i.e., the deterministic quasi-cyclic array code (QCAC) matrix and -sparse random binary matrix [-SRBM] are exploited. We demonstrate that the proposed CS encoders lead to comparable recovery performance. And efficient VLSI architecture designs are proposed for QCAC-CS and -SRBM encoders with reduced area and total power consumption.
Autors: Wenfeng Zhao;Biao Sun;Tong Wu;Zhi Yang;
Appeared in: IEEE Transactions on Biomedical Circuits and Systems
Publication date: Feb 2018, volume: 12, issue:1, pages: 242 - 254
Publisher: IEEE
 
» On-the-Fly Adaptive ${k}$ -Space Sampling for Linear MRI Reconstruction Using Moment-Based Spectral Analysis
Abstract:
In high-dimensional magnetic resonance imaging applications, time-consuming, sequential acquisition of data samples in the spatial frequency domain (-space) can often be accelerated by accounting for dependencies in linear reconstruction, at the cost of noise amplification that depends on the sampling pattern. Common examples are support-constrained, parallel, and dynamic MRI, and -space sampling strategies are primarily driven by image-domain metrics that are expensive to compute for arbitrary sampling patterns. It remains challenging to provide systematic and computationally efficient automatic designs of arbitrary multidimensional Cartesian sampling patterns that mitigate noise amplification, given the subspace to which the object is confined. To address this problem, this paper introduces a theoretical framework that describes local geometric properties of the sampling pattern and relates them to the spread in the eigenvalues of the information matrix described by its first two spectral moments. This new criterion is then used for very efficient optimization of complex multidimensional sampling patterns that does not require reconstructing images or explicitly mapping noise amplification. Experiments with in vivo data show strong agreement between this criterion and traditional, comprehensive image-domain- and -space-based metrics, indicating the potential of the approach for computationally efficient (on-the-fly), automatic, and adaptive design of sampling patterns.
Autors: Evan Levine;Brian Hargreaves;
Appeared in: IEEE Transactions on Medical Imaging
Publication date: Feb 2018, volume: 37, issue:2, pages: 557 - 567
Publisher: IEEE
 

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