An improved RIP-based performance guarantee for sparse signal reconstruction with noise via orthogonal matching pursuit

Ling Hua Chang, Jwo-Yuh Wu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Stability of sparse signal reconstruction in the noisy case via orthogonal matching pursuit has been widely studied in the literature of compressive sensing. To guarantee exact support identification under l2 / l-norm bounded noise, sufficient conditions, characterized in terms of the restricted isometry constant and the minimum magnitude of the signal components, were reported in [2]. In this paper, we derive a less conservative set of sufficient conditions of the same kind. Our analyses exploit a newly developed 'near-orthogonality' condition, which specifies the achievable angles between two compressed orthogonal sparse vectors. Thus, our improved performance guarantee benefits from more explicit knowledge about the geometry of the compressed space.

Original languageEnglish
Title of host publicationProceedings of 2014 International Symposium on Information Theory and Its Applications, ISITA 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages70-74
Number of pages5
ISBN (Electronic)9784885522925
StatePublished - 8 Dec 2014
Event2014 International Symposium on Information Theory and Its Applications, ISITA 2014 - Melbourne, Australia
Duration: 26 Oct 201429 Oct 2014

Publication series

NameProceedings of 2014 International Symposium on Information Theory and Its Applications, ISITA 2014

Conference

Conference2014 International Symposium on Information Theory and Its Applications, ISITA 2014
Country/TerritoryAustralia
CityMelbourne
Period26/10/1429/10/14

Keywords

  • compressive sensing
  • orthogonal matching pursuit (OMP)
  • restricted isometry constant (RIC)
  • restricted isometry property (RIP)

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