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dc.contributor.authorJahanshahi, J. A.
dc.contributor.authorDanyali, H.
dc.contributor.authorHelfroush, M. S.
dc.date.accessioned2018-06-18T12:49:20Z
dc.date.available2018-06-18T12:49:20Z
dc.date.issued2018-06cs
dc.identifier.citationRadioengineering. 2018 vol. 27, č. 2, s. 587-594. ISSN 1210-2512cs
dc.identifier.issn1210-2512
dc.identifier.urihttp://hdl.handle.net/11012/83043
dc.description.abstractThis paper considers sparsity-aware adaptive compressed sensing acquisition and the joint reconstruction of intra- and inter-correlated signals in the wireless sensor networks via distributed compressed sensing. textcolor{red}{ Due to the different sparsity order of the finite-length signals, we develop an adaptive sensing framework based on the sparsity order, in which sensor readings are sampled according to its own sparsity order measure.} On the decoder side, utilizing a distributed compressive sensing scheme, a joint reconstruction method is proposed to recover signal ensemble even in imperfect data communication. textcolor{red}{Moreover, we explore that by adapting the sampling rate of the sensed signals, not only the whole required number of measurements is reduced, but also the reconstruction performance is significantly improved. Numerical experiments verify that our proposed algorithm achieves higher reconstruction accuracy with a smaller number of required transmission, and with lower complexity as compared to those of the state of the art CS methods.en
dc.formattextcs
dc.format.extent587-594cs
dc.format.mimetypeapplication/pdfen
dc.language.isoencs
dc.publisherSpolečnost pro radioelektronické inženýrstvícs
dc.relation.ispartofRadioengineeringcs
dc.relation.urihttps://www.radioeng.cz/fulltexts/2018/18_02_0587_0594.pdfcs
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectSparsity measureen
dc.subjectsparsity-aware distributed compressed sensingen
dc.subjectcompressive sensingen
dc.titleA Distributed Compressed Sensing-based Algorithm for the Joint Recovery of Signal Ensembleen
eprints.affiliatedInstitution.facultyFakulta eletrotechniky a komunikačních technologiícs
dc.coverage.issue2cs
dc.coverage.volume27cs
dc.identifier.doi10.13164/re.2018.0587en
dc.rights.accessopenAccessen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen


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Creative Commons Attribution 4.0 International
Except where otherwise noted, this item's license is described as Creative Commons Attribution 4.0 International