Number of measurements in sparse signal recovery

Paul Tune*, Sibi Raj Bhaskaran, Stephen Hanly

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

11 Citations (Scopus)

Abstract

We 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.

Original languageEnglish
Title of host publication2009 IEEE International Symposium on Information Theory, ISIT 2009
Place of PublicationPiscataway, N.J.
Pages16-20
Number of pages5
DOIs
Publication statusPublished - 2009
Externally publishedYes
Event2009 IEEE International Symposium on Information Theory, ISIT 2009 - Seoul, Korea, Republic of
Duration: 28 Jun 20093 Jul 2009

Other

Other2009 IEEE International Symposium on Information Theory, ISIT 2009
CountryKorea, Republic of
CitySeoul
Period28/06/093/07/09

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