Results 21 to 30 of about 63,884 (167)
Communication-Efficient Distributed SGD With Compressed Sensing [PDF]
IEEE Control Systems Letters, 2022 We consider large scale distributed optimization over a set of edge devices connected to a central server, where the limited communication bandwidth between the server and edge devices imposes a significant bottleneck for the optimization procedure. Inspired by recent advances in federated learning, we propose a distributed stochastic gradient descent (
Yujie Tang +3 more
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IEEE Photonics Journal, 2021 The problem of long-distance imaging through time-varying scattering media, such as the atmosphere, is encountered in many science fields. Recent studies have demonstrated that random atmospheric variability can be considered a spatial light modulator in
Xuelin Lei +6 more
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A Compressed Sensing Approach for Distribution Matching [PDF]
2018 IEEE International Symposium on Information Theory (ISIT), 2018 In this work, we formulate the fixed-length distribution matching as a Bayesian inference problem. Our proposed solution is inspired from the compressed sensing paradigm and the sparse superposition (SS) codes. First, we introduce sparsity in the binary source via position modulation (PM).
Laurent Schmalen +2 more
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Leida xuebao, 2020 High-resolution wide-swath SAR moving target imaging is of great significance for target tracking. To achieve target tracking, conversional space-based multichannel SAR technology requires a large number of channels.
PAN Jie +3 more
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Frontiers in Energy Research, 2022 The current disturbance classification of power quality data often has the problem of low disturbance recognition accuracy due to its large volume and difficult feature extraction.
Xin Xia +6 more
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On the Performance of Turbo Signal Recovery with Partial DFT Sensing Matrices [PDF]
, 2015 This letter is on the performance of the turbo signal recovery (TSR) algorithm for partial discrete Fourier transform (DFT) matrices based compressed sensing.
Ma, Junjie, Ping, Li, Yuan, Xiaojun
core +1 more source
Joint recovery algorithms using difference of innovations for distributed compressed sensing [PDF]
, 2013 Distributed compressed sensing is concerned with representing an ensemble of jointly sparse signals using as few linear measurements as possible. Two novel joint reconstruction algorithms for distributed compressed sensing are presented in this paper ...
Coluccia, Giulio +2 more
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Harmonic analysis in distributed power system based on IoT and dynamic compressed sensing
Energy Reports, 2022 Massive distributed clean energy takes power electronic equipment as the grid access connector, which brings serious harmonic pollutions. To monitor the power quality in the massive distributed power systems, this paper proposes a real-time harmonic ...
Yuqing Niu +5 more
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Efficient distributed storage strategy based on compressed sensing for space information network
International Journal of Distributed Sensor Networks, 2016 This article investigates the distributed data storage problem with compressed sensing in the space information network. Since there exists a performance-energy trade-off, most existing strategies focus only on improving the compressed sensing ...
Bo Kong +4 more
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Distributed Basis Pursuit [PDF]
, 2012 We propose a distributed algorithm for solving the optimization problem Basis Pursuit (BP). BP finds the least L1-norm solution of the underdetermined linear system Ax = b and is used, for example, in compressed sensing for reconstruction.
Aguiar, Pedro M. Q. +3 more
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