Number of Measurements in Sparse Signal Recovery

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dc.creatorTune, Paul
dc.creatorPillai, Sibiraj Bhaskaran
dc.creatorHanly, Stephen
dc.date2009-04-29
dc.date.accessioned2026-07-07T13:09:53Z
dc.date.available2026-07-07T13:09:53Z
dc.descriptionWe analyze the asymptotic performance of sparse signal recovery from noisy measurements. In particular, we generalize some of the existing results for the Gaussian case to subgaussian and other ensembles. An achievable result is presented for the linear sparsity regime. A converse on the number of required measurements in the sub-linear regime is also presented, which cover many of the widely used measurement ensembles. Our converse idea makes use of a correspondence between compressed sensing ideas and compound channels in information theory.
dc.description6 pages, 1 figure. Extended from conference version with proofs included
dc.identifierhttps://arxiv.org/abs/0904.4525
dc.identifierhttp://arxiv.org/abs/0904.4525
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/228889
dc.subjectInformation Theory
dc.titleNumber of Measurements in Sparse Signal Recovery
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