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Artificial immune algorithm based signal reconstruction for compressive sensing

  • Harbin Institute of Technology
  • China Electronic Equipment System Engineering Corporation

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

Abstract

The core of compressive sensing, i.e., signal reconstruction, is a constraint of signal sparsity problem, which can be implemented by l0 norm minimization. But l0 norm minimization requires exhaustively listing all possibility of the original signals, which is an NP-hard problem to achieve difficultly by traditional algorithm.This paper proposes a signal reconstruction algorithm based on artificial immune algorithm, which can solve l0 norm minimization directly. It has been proved through numerical simulations that performance of signal reconstruction and photo-Acoustic image reconstruction based on the proposed method is superior to that of OMP algorithm.

Original languageEnglish
Title of host publication2014 IEEE International Instrumentation and Measurement Technology Conference
Subtitle of host publicationInstrumentation and Measurement for Sustainable Development, I2MTC 2014 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages76-81
Number of pages6
ISBN (Print)9781467363853
DOIs
StatePublished - 2014
Event2014 IEEE International Instrumentation and Measurement Technology Conference: Instrumentation and Measurement for Sustainable Development, I2MTC 2014 - Montevideo, Uruguay
Duration: 12 May 201415 May 2014

Publication series

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

Conference

Conference2014 IEEE International Instrumentation and Measurement Technology Conference: Instrumentation and Measurement for Sustainable Development, I2MTC 2014
Country/TerritoryUruguay
CityMontevideo
Period12/05/1415/05/14

Keywords

  • Artificial Immune Algorithm
  • Compressive sensing
  • Signal reconstruction

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