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2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018

作者： Chin, Sang Peter Tran, Trac D. Tran, Dung Rangamani, Akshay Department of Computer Science Boston University BostonMA United States Electrical and Computer Engineering Department Johns Hopkins University BaltimoreMD United States

ISBN: (纸本)9781538646588

In this paper we study the unmixing problem which aims to separate a set of structured signals from their superposition. In this paper, we consider the scenario in which the mixture is observed via nonlinear compressive measurements. We present a fast, robust, greedy algorithm called Unmixing Matching pursuit (UnmixMP) to solve this problem. We prove rigorously that the algorithm can recover the constituents from their noisy nonlinear compressive measurements with arbitrarily small error. We compare our algorithm to the Demixing with Hard Thresholding (DHT) algorithm [1], in a number of experiments on synthetic and real data. © 2018 IEEE.

关键词： Dictionaries Matching pursuit algorithms Signal processing algorithms pursuit algorithms Sensors Convergence Robustness"

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Unconstrained monitoring of body motion during walking

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IEEE ENGINEERING IN MEDICINE AND BIOLOGY MAGAZINE 2003年第3期22卷 104-109页

作者： Akay, M Sekine, M Tamura, T Higashi, Y Fujimoto, T Dartmouth Coll Thayer Sch Engn Neural Engn & Informat Lab Hanover NH 03755 USA

Discusses using the matching pursuit algorithm to characterize time-frequency patterns of body motion in poststroke hemiplegic patients. We have been working on the quantification of body motions in healthy young and elderly subjects, patients with Parkinson's disease (PD), and poststroke hemiplegic (PSH) patients using an accelerometry technique and advanced signal processing methods. In this article, we use the matching pursuit (MP) algorithm to characterize the time-frequency patterns of the acceleration signal recorded from both healthy subjects and poststroke hemilpegic patients. The MP algorithm was chosen since it provides better time and frequency resolutions than other time-frequency analysis methods and is an algorithm that decomposes any signal into several already-known time-frequency patterns, which are called atoms. It also provides detailed information about each time-frequency pattern including its energy, time and frequency localization, and phase and scale (time duration), which can be used for the comparison and the statistical analysis.

关键词： Legged locomotion Matching pursuit algorithms Signal processing algorithms Time frequency analysis pursuit algorithms Patient monitoring Senior citizens Parkinson's disease Acceleration Energy resolution

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Real-Time Data Sensing for Microseismic Monitoring via Adaptive Compressed Sampling

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IEEE SENSORS JOURNAL 2023年第10期23卷 10644-10655页

作者： Chen, Liang Lan, Zhiqiang Qian, Shuo Hou, Xiaojuan Zhang, Le He, Jian Chou, Xiujian North Univ China State Sci & Technol Elect Test & Measurement Lab Taiyuan 030051 Shanxi Peoples R China Soochow Univ Sch Future Sci & Engn Suzhou 215299 Peoples R China North Univ China Sch Software Taiyuan 030051 Shanxi Peoples R China

The large amount of monitoring data has posed enormous challenges to the quick response and accurate analysis of microseismic events. Compressed sensing (CS) has the advantages of low resource cost, high efficiency, and excellent data compression ratio (CR), over conventional sensing methods. However, there are still issues to be addressed for its applications: 1) the poor quality and complex signal structure significantly increased the difficulty of keeping satisfactory efficiency;2) the systematic design of the sparse dictionary, and the measurement matrix for microseismic signal CS are still poor;and 3) the conventional recovery algorithms also require prior knowledge of signal sparsity, which is hardly possible to know or estimate in practice. Therefore, an adaptive real-time sensing method for microseismic monitoring from the perspective of systematic design was proposed in this work. We first analyzed noise and signal structure characteristics to construct an over-complete learning dictionary. Second, according to the learned dictionary, we analyzed the key performance factors of random projection through comparison between different matrices. Third, we explored the relationship between the signal sparsity and the residual energy decay during data recovery with the greedy pursuit algorithms and then presented an energy-ratio-based sparsity adaptive matching algorithm. Finally, we carried out the performance evaluation of the proposed real-time sensing method through synthetic signals and field monitoring data.

关键词： Sensors Dictionaries Sparse matrices Monitoring pursuit algorithms Noise measurement Matching pursuit algorithms Compressed sensing (CS) microseismic monitoring real-time sensing sparsity adaptive

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The cosparse analysis model and algorithms

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APPLIED AND COMPUTATIONAL HARMONIC ANALYSIS 2013年第1期34卷 30-56页

作者： Nam, S. Davies, M. E. Elad, M. Gribonval, R. Ctr Rech INRIA Rennes Bretagne Atlantique F-35042 Rennes France Univ Edinburgh Sch Engn & Elect Edinburgh EH9 3JL Midlothian Scotland Technion Israel Inst Technol Dept Comp Sci IL-32000 Haifa Israel

After a decade of extensive study of the sparse representation synthesis model, we can safely say that this is a mature and stable field, with clear theoretical foundations, and appealing applications. Alongside this approach, there is an analysis counterpart model, which, despite its similarity to the synthesis alternative, is markedly different. Surprisingly, the analysis model did not get a similar attention, and its understanding today is shallow and partial. In this paper we take a closer look at the analysis approach, better define it as a generative model for signals, and contrast it with the synthesis one. This work proposes effective pursuit methods that aim to solve inverse problems regularized with the analysis-model prior, accompanied by a preliminary theoretical study of their performance. We demonstrate the effectiveness of the analysis model in several experiments, and provide a detailed study of the model associated with the 2D finite difference analysis operator, a close cousin of the TV norm. (C) 2012 Elsevier Inc. All rights reserved.

关键词： Synthesis Analysis Sparse representations Union of subspaces pursuit algorithms Greedy algorithms Compressed-sensing

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An Optimal Guidance Strategy for Moving-Target Interception by a Multirotor Unmanned Aerial Vehicle Swarm

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IEEE ACCESS 2020年 8卷 121650-121664页

作者： Wang, Xi Tan, Guanzheng Dai, Yusi Lu, Fanlei Zhao, Jian Cent South Univ Sch Automat Changsha 410083 Peoples R China

To solve the problem of intercepting a moving target by a multirotor unmanned aerial vehicle (UAV) swarm, an optimal guidance strategy is proposed. The proposed guidance law is based on the integration of the classic pure pursuit guidance law and Kuhn-Munkres (KM) optimal matching algorithm, and virtual force potential functions are used to avoid collision. The proposed optimal guidance strategy is demonstrated by simulation experiments. The simulation results indicate that with the proposed optimal guidance strategy, a UAV swarm can intercept a moving target while maintaining the predetermined formation, and during the formation flight, the collisions between UAVs or the target can be avoided. Through a comparative experiment, the proposed optimal matching algorithm is proven to significantly reduce the average per-sampling-period total flight distance of all the UAVs and accelerate the interception process, and the formation completion degree is improved.

关键词： Optimal matching unmanned aerial vehicles pursuit algorithms three-dimensional guidance law target interception collision avoidance

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MATCHING pursuitS WITH TIME-FREQUENCY DICTIONARIES

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 1993年第12期41卷 3397-3415页

作者： MALLAT, SG ZHANG, ZF NYU COURANT INST MATH SCI DEPT MATH NEW YORK NY 10012 USA

We introduce an algorithm, called matching pursuit, that decomposes any signal into a linear expansion of waveforms that are selected from a redundant dictionary of functions. These waveforms are chosen in order to best match the signal Structures. Matching pursuits are general procedures to compute adaptive signal representations. With a dictionary of Gabor functions a matching pursuit defines an adaptive time-frequency transform. We derive a signal energy distribution in the time-frequency plane, which does not include interference terms, unlike Wigner and Cohen class distributions. A matching pursuit isolates' the signal structures that are coherent with respect to a given dictionary. Gn application to pattern extraction from noisy signals is described. We compare a matching pursuit decomposition with a signal expansion over an optimized wavepacket orthonormal basis, selected with the algorithm of Coifman and Wickerhauser.

关键词： Matching pursuit algorithms Time frequency analysis Dictionaries pursuit algorithms Fourier transforms Signal representations Vocabulary Signal processing algorithms Interference Natural languages

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Gearbox Fault Diagnosis Using Multiscale Sparse Frequency-Frequency Distributions

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IEEE ACCESS 2021年 9卷 113089-113099页

作者： Zhang, Luke Li, Yi Dong, Lincheng Yang, Xiaoqing Ding, Xiaoxi Zeng, Qiang Wang, Liming Shao, Yimin Nucl Power Inst China Sci & Technol Reactor Syst Design Technol Lab Chengdu 610213 Peoples R China Chongqing Univ Coll Mech Engn Chongqing 400044 Peoples R China Chongqing Univ State Key Lab Mech Transmiss Chongqing 400044 Peoples R China

Gear fault related information is distributed over a broad frequency band, indicating a complex modulation mechanism. It is difficult to detect early-stage gear faults accurately by detecting fault frequencies in a limited frequency band. This paper proposes a novel method for achieving fault frequency detection more effectively. A short-frequency Fourier transform with a series of frequency-window functions is initially used to obtain the overall frequency information of a vibration signal. Subsequently, based on sparse decomposition and orthogonal matching pursuit, harmonic atoms are applied to refine modulation components from multiscale pseudo mono-components. A multiscale-sparse frequency-frequency distribution is eventually applied to augment existing fault-related harmonic components. In addition, a synthesized sparse spectrum is acquired by determining the frequency-frequency ridge from the multiscale sparse frequency-frequency distribution. Compared with empirical-mode-decomposition and fast-kurtogram analyses, the effectiveness and superiority of the proposed method for gear fault detection have been verified via experiments.

关键词： Fault diagnosis Vibrations Frequency synthesizers Frequency modulation Fourier transforms Gears Fault detection Demodulation fault detection Fourier transforms gears modulation pursuit algorithms sparse matrices spectral analysis vibrations windows

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ASSOCIATIVE LEARNING OF BOOLEAN FUNCTIONS

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IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS 1989年第5期19卷 1008-1015页

作者： MUKHOPADHYAY, S THATHACHAR, MAL CONCORDIA UNIV DEPT ELECT & COMP ENGNMONTREAL H3G 1M8QUEBECCANADA

A cooperative-game-playing learning automata model is presented for a complex nonlinear associative task, namely, learning of Boolean functions. The unknown Boolean function is expressed in terms of minterms, and a team of automata is used to learn the minterms present in the expansion. Only noisy outputs of the Boolean function are assumed to be available for the team of automata that use a variation of the rapidly converging estimator learning algorithm called the pursuit algorithm. A divide-and-conquer approach is proposed to overcome the storage and computational problems of the pursuit algorithm. Extensive simulation experiments have been carried out for six-input Boolean tasks. The main advantages offered by the model are generality, proof of convergence, and fast learning.

关键词： Teams Boolean functions pursuit algorithms State Dependent Learning Associative learning Automata

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Model-Based Control for Power Converters With Variable Sampling Time: A Case Example Using Five-Phase Induction Motor Drives

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2019年第8期66卷 5800-5809页

作者： Arahal, Manuel R. Martin, Cristina Barrero, Federico Gonzalez-Prieto, Ignacio Duran, Mario J. Univ Seville Syst & Automat Engn Dept Seville 41092 Spain Univ Seville Dept Elect Engn Seville 41092 Spain Univ Huelva Elect & Thermal Engn Dept Huelva 21819 Spain Univ Malaga Dept Elect Engn E-29071 Malaga Spain

Discrete-time control of power converters without modulation blocks have been considered in recent times in modern high-performance electromechanical drives, particularly with the appearance of model predictive control in its finite set version. The shortcomings produced by the fixed discretization of time used in this kind of control systems has been analyzed, and several methods have been put forward to deal with them. Most of the alternatives increase the complexity of the controller introducing different analytical modulation methods. However, a variable sampling time can be a simpler and more natural solution, at the expense of using a less-known paradigm for implementation. This paper introduces a new control approach based on a model of the system as in predictive controllers but using variable sampling time. It can be applied to modern power converters and drives, including conventional three-phase or advanced multiphase ones. Experimental results are provided to test the ability of the controller using a five-phase induction motor drive as a case example.

关键词： Digital control systems nonuniform sampling power conversion predictive control pursuit algorithms

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Plate impulse response spatial interpolation with sub-Nyquist sampling

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JOURNAL OF SOUND AND VIBRATION 2011年第23期330卷 5678-5689页

作者： Chardon, G. Leblanc, A. Daudet, L. ESPCI CNRS UMR 7587 Inst Langevin Ondes & Images F-75231 Paris 05 France Univ Lille Nord France F-59000 Lille France LGCgE UArtois F-62400 Bethune France Paris Diderot Univ Paris France Inst Univ France Paris France

Impulse responses of vibrating plates are classically measured on a fine spatial grid satisfying the Shannon-Nyquist spatial sampling criterion, and interpolated between measurement points. For homogeneous and isotropic plates, this study proposed a more efficient sampling and interpolation process, inspired by the recent paradigm of compressed sensing. Remarkably, this method can accommodate any star-convex shape and unspecified boundary conditions. Here, impulse responses are first decomposed as sums of damped sinusoids, using the Simultaneous Orthogonal Matching pursuit algorithm. Finally, modes are interpolated using a plane wave decomposition. As a beneficial side effect, these algorithms can also be used to obtain the dispersion curve of the plate with a limited number of measurements. Experimental results are given for three different plates of different shapes and boundary conditions, and compared to classical Shannon interpolation. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Side Effect Interpolation vibrating plate pursuit algorithms IMPULSE RESPONSE Matching pursuit algorithms Boundary conditions Isotropic

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