An improved RIP-based performance guarantee for sparse signal recovery via orthogonal matching pursuit

Ling Hua Chang, Jwo-Yuh Wu

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

3 Scopus citations

Abstract

A sufficient condition reported very recently for perfect recovery of a K-sparse vector via orthogonal matching pursuit in K iterations is that the restricted isometry constant of the sensing matrix satisfies δK+1 < 1/(√K + 1). By exploiting a 'near orthogonality' condition specified in terms of the achievable angles between two orthogonal sparse vectors upon compression, this paper shows that the requirement on δK+1 can be further relaxed to δk+1 < √4k+1 - 1\2K. This result thus narrows the gap between the so far best known bound and the ultimate performance guarantee δK+1 < 1/√K that is conjectured by Dai and Milenkovic in 2009.

Original languageEnglish
Title of host publicationISCCSP 2014 - 2014 6th International Symposium on Communications, Control and Signal Processing, Proceedings
PublisherIEEE Computer Society
Pages28-31
Number of pages4
ISBN (Print)9781479928903
DOIs
StatePublished - 1 Jan 2014
Event6th International Symposium on Communications, Control and Signal Processing, ISCCSP 2014 - Athens, Greece
Duration: 21 May 201423 May 2014

Publication series

NameISCCSP 2014 - 2014 6th International Symposium on Communications, Control and Signal Processing, Proceedings

Conference

Conference6th International Symposium on Communications, Control and Signal Processing, ISCCSP 2014
Country/TerritoryGreece
CityAthens
Period21/05/1423/05/14

Keywords

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

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