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J. Sens. Actuator Netw. 2014, 3(1), 1-25; doi:10.3390/jsan3010001
Article

Methods for Distributed Compressed Sensing

* ,
 and
School of Electrical Engineering and ACCESS Linneaus Centre, KTH Royal Institute of Technology, Stockholm SE-100 44, Sweden
* Author to whom correspondence should be addressed.
Received: 15 October 2013 / Revised: 29 November 2013 / Accepted: 9 December 2013 / Published: 23 December 2013
(This article belongs to the Special Issue Feature Papers)
View Full-Text   |   Download PDF [360 KB, 30 December 2013; original version 23 December 2013]   |  

Abstract

Compressed sensing is a thriving research field covering a class of problems where a large sparse signal is reconstructed from a few random measurements. In the presence of several sensor nodes measuring correlated sparse signals, improvements in terms of recovery quality or the requirement for a fewer number of local measurements can be expected if the nodes cooperate. In this paper, we provide an overview of the current literature regarding distributed compressed sensing; in particular, we discuss aspects of network topologies, signal models and recovery algorithms.
Keywords: distributed compressed sensing; distributed greedy pursuit; greedy algorithms distributed compressed sensing; distributed greedy pursuit; greedy algorithms
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).
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Sundman, D.; Chatterjee, S.; Skoglund, M. Methods for Distributed Compressed Sensing. J. Sens. Actuator Netw. 2014, 3, 1-25.

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