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Methods for Distributed Compressed Sensing
KTH, School of Electrical Engineering (EES), Communication Theory. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
KTH, School of Electrical Engineering (EES), Communication Theory. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0003-2638-6047
KTH, School of Electrical Engineering (EES), Communication Theory. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0002-7926-5081
2014 (English)In: Journal of Sensor and Actuator Networks, ISSN 2224-2708, Vol. 3, no 1, 1-25 p.Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
2014. Vol. 3, no 1, 1-25 p.
Keyword [en]
distributed compressed sensing, distributed greedy pursuit, greedy algorithms
National Category
Signal Processing Communication Systems Telecommunications
Identifiers
URN: urn:nbn:se:kth:diva-137057DOI: 10.3390/jsan3010001OAI: oai:DiVA.org:kth-137057DiVA: diva2:677783
Funder
A multiscale, cross‐disciplinary approach to the study of climate change effect on ecosystem services and biodiversity
Note

QC 20150217

Available from: 2013-12-10 Created: 2013-12-10 Last updated: 2015-02-17Bibliographically approved

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Saikat, ChatterjeeSkoglund, Mikael

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