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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： S.F. Giszter Department of Neurobiology and Anatomy MCPHU Philadelphia USA

It has been proposed that the segmental spinal nervous system may organize movement using a collection of force-field primitives. The temporal organization of primitives has not been examined in detail. Recent data examining muscle activity underlying corrections of motor patterns suggested that primitives might be recruited into motor programs as waveforms with a constant duration. Here we test the idea that each primitive or premotor drive comprising part of the motor patterns might be expressed as the combination of a small number of time-frequency atoms from some orthonormal basis. We analyze the temporal organization of pre-motor drives extracted from the motor pattern by the Bell-Sejnowski algorithm for independent component analysis. We then use matching pursuit cosine packet analysis to examine the time series of the activation waveforms of each of the independent components. The analysis confirms that the motor pattern can be described as a combination of a small number of time-frequency atoms. These atoms combine to generate the temporal structure and activation of the individual components or premotor drives that generate individual muscle activity.

关键词： matching pursuit algorithms Quantization Time frequency analysis Independent component analysis pursuit algorithms Muscles Pattern analysis Nervous system Recruitment Testing

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Designing frames for matching pursuit algorithms

Designing frames for matching pursuit algorithms

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： K. Engan S.O. Aase J.H. Husoy Department of Electrical and Computer Technology Stavanger College Stavanger Norway

A technique for designing frames to use with vector selection algorithms, for example matching pursuits (MP), is presented. The design algorithm is iterative and requires a training set of signal vectors. An MP algorithm chooses frame vectors to approximate each training vector. Each vector in the frame is then adjusted by using the residuals for the training vectors which used that particular frame vector in their expansion. The frame design algorithm is applied to speech and electrocardiogram (ECG) signals, and the designed frames are tested on signals outside the training sets. Experiments demonstrate that the approximation capabilities, in terms of mean square error (MSE), of the optimized frames are significantly better than those found using frames designed by ad hoc techniques. Experiments show typical reduction in MSE by 20-50%.

关键词： matching pursuit algorithms Algorithm design and analysis pursuit algorithms Iterative algorithms Signal design Speech Electrocardiography Testing Mean square error methods Design optimization

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Sparse electromagnetic tomography based on matching pursuit algorithms

Sparse electromagnetic tomography based on matching pursuit ...

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IEEE Instrumentation and Measurement Technology Conference

作者： Yang Tao Wenbo Zhang Yifei Zhao Christos Ktistis Wuliang Yin Anthony J. Peyton School of Electrical and Electronic Engineering The University of Manchester Manchester U.K.

ISBN: (纸本)9781467392211

A sparse Electromagnetic Tomography (EMT) system based on matching pursuit (MP) algorithms is introduced in this paper. The sparse EMT problem with a linear model is essentially a pursuit for the sparse representation of the spatial conductivity. The framework of sparse representation theory is adopted for the EMT problem. Such notations as spark and mutual-coherence are introduced as tools in the analysis of the recovery results. MP algorithms are considered as effective and efficient solvers towards sparse representation. Some variations of MP are compared in this paper for a random dictionary and the EMT dictionary. The result of conductivity reconstruction proves the effectiveness of MP algorithms for the proposed EMT system.

关键词： matching pursuit algorithms Dictionaries Coils Atomic measurements Conductivity Image reconstruction Sensors

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Delay-Doppler search for matching pursuit algorithms in time-variant channels

Delay-Doppler search for matching pursuit algorithms in time...

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IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)

作者： Nasimi Eldarov Guoping Tan Thorsten Herfet Telecommunications Lab Saarland University Saarbrücken Germany College of Computer and Information Engineering Hohai University Nanjing China

The development of wireless communications created broad opportunities in mobile communications. However, poor channel estimation and lack of proper Doppler shift compensation techniques limit the mobility considerably. Therefore, a high quality and low-complexity channel estimation is one of the most important conditions for high mobility. In this paper we propose a low-complexity delay-Doppler search (DDS) for matching pursuit algorithms. The proposed search algorithm can be applied to MP algorithms which estimates the delay and the Doppler features of the channel in two dimensions efficiently. Two dimensional approach lowers the complexity significantly. At the end we show results for the DVB-T2 systems.

关键词： Delays Doppler shift matching pursuit algorithms Channel estimation Dictionaries Complexity theory Noise

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Adaptive resolution by matching pursuit algorithms

Adaptive resolution by matching pursuit algorithms

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European Signal Processing Conference (EUSIPCO)

作者： Güneş Karabulut Abbas Yongaçog̃lu Tolga Kurt School of Information Technology and Engineering University of Ottawa Ottawa Ontario Canada

The family of matching pursuit algorithms are greedy heuristic methods for basis selection problem. In this paper, we propose an adaptive structure for matching pursuit algorithms that uses a progressive refinement structure. The proposed adaptive algorithm allows the detector to adjust the tradeoff between the computational complexity and the resolution performance. The novel algorithm is applied to direction of arrival detection problem and it is shown that the algorithm results in a lower computational complexity than the direct implementation of matching pursuit algorithms.

关键词： matching pursuit algorithms Vectors Dictionaries Direction-of-arrival estimation Approximation algorithms Signal to noise ratio Computational complexity

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Performance limits of matching pursuit algorithms

Performance limits of matching pursuit algorithms

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IEEE International Symposium on Information Theory

作者： Yuzhe Jin Bhaskar D. Rao Department of Electrical and Computer Engineering University of California San Diego CA USA

ISBN: (纸本)9781424422562

In this paper, we examine the performance limits of the Orthogonal matching pursuit (OMP) algorithm, which has proven to be effective in solving for sparse solutions to inverse problem arising in overcomplete representations. To identify these limits, we exploit the connection between sparse solution problem and multiple access channel (MAC) in wireless communication domain. The forward selective nature of OMP helps it to be recognized as a successive interference cancellation (SIC) scheme that decodes non-zero entries one at a time in a specific order. We leverage this SIC decoding order and utilize the criterion for successful decoding to develop the information-theoretic performance limitation for OMP, which involves factors such as dictionary dimension, signal-to-noise-ratio, and importantly, the relative behavior of the non- zeros entries. Supported by computer simulations, our proposed criterion is demonstrated to be asymptotically effective in explaining the behavior of OMP.

关键词： matching pursuit algorithms Decoding Dictionaries Silicon carbide Noise measurement Signal to noise ratio Gain

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Orthogonal matching pursuit-Based algorithms for the Birkhoff-Von Neumann Decomposition

Orthogonal Matching Pursuit-Based Algorithms for the Birkhof...

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European Signal Processing Conference (EUSIPCO)

作者： Damien Lesens Jérémy E. Cohen Bora Uçar LIP ENS de Lyon 46 allée d'Italie Lyon France Univ Lyon INSA-Lyon UCBL UJM CNRS Inserm CREATIS UMR 5220 U1294 Lyon France CNRS and LIP UMR5668 (Université de Lyon - ENS de Lyon - UCBL - CNRS - Inria) 46 allée d'Italie Lyon France

ISBN: (数字)9789464593617

ISBN: (纸本)9798331519773

Birkhoff-von Neumann (BvN) decomposition writes a doubly stochastic matrix as a convex combination of permutation matrices. For a given doubly stochastic matrix, the decom-position in general is not unique. In many applications a sparsest decomposition, that is with the smallest number of permutation matrices is of interest. This problem is known to be NP-complete, and heuristics are used to obtain sparse solutions. We propose heuristics based on the well-known orthogonal matching pursuit for sparse BvN decomposition. We experimentally compare our heuristics with the state of the art from the literature and show how our methods advance the known heuristics.

关键词： Heuristic algorithms matching pursuit algorithms Signal processing algorithms Europe Signal processing Matrix decomposition Sparse matrices Optimization

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FPGA Implementation of Staged Projection Refining Multiple Orthogonal matching pursuit Algorithm for Compressed Sensing

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IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS 2025年第5期33卷 1334-1347页

作者： Liu, Sujuan Liang, Yichen Zhang, Zixing Wan, Peiyuan Beijing Univ Technol Coll Microelect Beijing 100124 Peoples R China

Reconstruction algorithms are an integral part of compressed sensing (CS) theory, which can reliably reconstruct the original signal from the low-dimensional compressed signal. The orthogonal matching pursuit (OMP) algorithm has been widely studied and extensively selected in hardware implementations. However, the low reconstruction success rate of the OMP algorithm under high sparsity conditions has led to the proposal and application of more reconstruction algorithms in hardware implementations. In this article, a staged projection refining multiple OMP (SPR-MOMP) algorithm is proposed based on the OMP algorithm. This algorithm improves the reconstruction accuracy by refining the support set using a staged backtracking strategy. It also employs a multiple-atom selection strategy for parallel expansion of the support set, ensuring reconstruction efficiency. The reconstruction simulation demonstrates that the SPR-MOMP algorithm achieves a higher reconstruction success rate than the OMP algorithm, with fewer iterations. A hardware architecture applying the SPR-MOMP algorithm is designed and implemented on a Virtex UltraScale+ field-programmable gate array (FPGA) with N = 1024, M = 256, and K = 36. The proposed architecture achieves a reconstruction signal-to-noise ratio (RSNR) of 44.27 dB, with 20-bit data width and 15-bit fractional width. The maximum clock frequency of the architecture is 200 MHz, enabling reconstruction within 276.6 mu s. The proposed architecture achieves a lower dynamic power consumption of 1929 mW.

关键词： Computer architecture matching pursuit algorithms Hardware Field programmable gate arrays Image reconstruction Heuristic algorithms Backtracking Reconstruction algorithms Signal processing algorithms Sensors Compressed sensing (CS) field-programmable gate array (FPGA) hardware reconstruction orthogonal matching pursuit (OMP) QR decomposition (QRD)

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Optimizing Power Quality Signal Compression: Harnessing Compressed Sensing and Reconstruction Techniques for Big Data Measurement

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IEEE ACCESS 2025年 13卷 36339-36347页

作者： Ruiz, Milton Garcia, Edwin Univ Politecn Salesiana Dept Elect Engn GIREI Res Grp Quito 170525 Ecuador

The following research proposes a compression technique that combines traditional lossy compression methods with newer ones to identify properties of power quality signals. The data collected undergoes biorthogonal wavelet transformation and filter integration to remove the ripple added to the signal. The system utilizes matching pursuit to create an orthogonal dictionary, achieving compression ratios of 846:1. The quality indicators achieved are Percentage of Retained Energy (RTE) =0.9969, Normalized Mean Squared Error NMSE =0.0030, and Correlation (COR) =0.9969, demonstrating the technique's efficiency. This research's results surpass the most relevant papers in Q1 journals.

关键词： matching pursuit algorithms Power quality Vectors Dictionaries Loss measurement Smart meters Power measurement Meters Indexes Fluctuations big data matching pursuit signal processing lossless compression

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Optimal Client Selection of Federated Learning Based on Compressed Sensing

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IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY 2025年 20卷 1679-1694页

作者： Li, Qing Lyu, Shanxiang Wen, Jinming Guangxi Univ Sci & Technol Coll Comp Sci & Technol Liuzhou 545006 Peoples R China Jinan Univ Coll Cyber Secur Guangzhou 510632 Peoples R China Guangxi Coll & Univ Key Lab Intelligent Comp & Dis Liuzhou 545006 Peoples R China Jilin Univ Dept Math Changchun 130012 Peoples R China

Federated learning faces challenges associated with privacy breaches, client communication efficiency, stragglers' effect, and heterogeneity. To address these challenges, this paper reformulates the optimal client selection problem as a sparse optimization task, proposes a secure and efficient optimal client selection method for federated learning, named secure orthogonal matching pursuit federated learning (SecOMPFL). Therein, we first introduce a method to identify correlations in the local model parameters of participating clients, addressing the issue of duplicated client contributions highlighted in recent literature. Next, we establish a secure variant of the OMP algorithm in compressed sensing using secure multiparty computation and propose a novel secure aggregation protocol. This protocol enhances the global model's convergence rate through sparse optimization techniques while maintaining privacy and security. It relies entirely on the local model parameters as inputs, minimizing client communication requirements. We also devise a client sampling strategy without requiring additional communication, resolving the bottleneck encountered by the optimal client selection policy. Finally, we introduce a strict yet inclusive straggler penalty strategy to minimize the impact of stragglers. Theoretical analysis confirms the security and convergence of SecOMPFL, highlighting its resilience to stragglers' effect and systematic/statistical heterogeneity with high client communication efficiency. Numerical experiments were conducted to compare the convergence rate and client communication efficiency of SecOMPFL with those of FedAvg, FOLB, and BN2. These experiments used natural and synthetic with statistical heterogeneity datasets, considering varying numbers of clients and client sampling scales. The results demonstrate that SecOMPFL achieves a competitive convergence rate, with communication overhead 39.96% lower than that of FOLB and 28.44% lower than that of BN2. Fu

关键词： Convergence Security matching pursuit algorithms Protocols Optimization Data models Computational modeling Servers Resilience Federated learning compressed sensing optimal client selection secure multi-party computation

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