Results 21 to 30 of about 214,668 (274)
Model-based decentralized Bayesian algorithm for distributed compressed sensing [PDF]
Signal processing. Image communication, 2020 In this paper, a novel model-based distributed compressive sensing (DCS) algorithm is proposed. DCS exploits the inter-signal correlations and has the capability to jointly recover multiple sparse signals.
Razieh Torkamani +2 more
semanticscholar +1 more source
Distributed Compressive Sensing
CoRR, 2009 42 pages, 6 figures.
Dror Baron +4 more
openaire +3 more sources
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
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).
Mohamad Dia +2 more
openaire +2 more sources
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
core +2 more sources
Operational Rate-Distortion Performance of Single-source and Distributed Compressed Sensing [PDF]
, 2014 We consider correlated and distributed sources without cooperation at the encoder. For these sources, we derive the best achievable performance in the rate-distortion sense of any distributed compressed sensing scheme, under the constraint of high--rate ...
Coluccia, Giulio +2 more
core +4 more sources
Multi-User Distributed Computing Via Compressed Sensing [PDF]
Information Theory Workshop, 2023 The multi-user linearly-separable distributed computing problem is considered here, in which N servers help to compute the real-valued functions requested by K users, where each function can be written as a linear combination of up to L (generally non ...
Ali Khalesi +3 more
semanticscholar +1 more source
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
core +3 more sources
Channel Impulse Response-based Distributed Physical Layer Authentication [PDF]
, 2017 In this preliminary work, we study the problem of {\it distributed} authentication in wireless networks. Specifically, we consider a system where multiple Bob (sensor) nodes listen to a channel and report their {\it correlated} measurements to a Fusion ...
Abbasi, Qammer H. +4 more
core +2 more sources
Distributed Representation of Geometrically Correlated Images with Compressed Linear Measurements [PDF]
, 2010 This paper addresses the problem of distributed coding of images whose correlation is driven by the motion of objects or positioning of the vision sensors. It concentrates on the problem where images are encoded with compressed linear measurements.
Frossard, Pascal +1 more
core +3 more sources