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A modified orthogonal matching algorithm using correlation coefficient for compressed sensing

  • Harbin Institute of Technology

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

Abstract

This paper presents a modified orthogonal matching pursuit (OMP) algorithm for compressed sensing (CS). Compared with the standard OMP algorithm, the most innovation of this algorithm is its improvement on the reconstruction probability of the sparse signal, and the basic idea is that the support set is estimated using correlation coefficient because the correlation coefficient can be viewed as a normalized matching criterion. In the standard OMP algorithm, the inner product is used for estimating the support set of the sparse signal, which may generate the wrong coordinates because the inner product couldn't guarantee the expected column of sensing matrix matches the measurement vector very best. However, the proposed algorithm is able to demonstrate a better performance on estimating the support set to some extent. From the simulation results, the proposed algorithm outperforms the standard OMP algorithm.

Original languageEnglish
Title of host publication2011 IEEE International Instrumentation and Measurement Technology Conference, I2MTC 2011 - Proceedings
Pages577-581
Number of pages5
DOIs
StatePublished - 2011
Event2011 IEEE International Instrumentation and Measurement Technology Conference, I2MTC 2011 - Binjiang, Hangzhou, China
Duration: 10 May 201112 May 2011

Publication series

NameConference Record - IEEE Instrumentation and Measurement Technology Conference
ISSN (Print)1091-5281

Conference

Conference2011 IEEE International Instrumentation and Measurement Technology Conference, I2MTC 2011
Country/TerritoryChina
CityBinjiang, Hangzhou
Period10/05/1112/05/11

Keywords

  • Compressed sensing
  • correlation coefficient
  • orthogonal matching pursuit
  • reconstruction probability

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