A note on support recovery of sparse signals using linear programming

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

Abstract

A new theory known as compressed sensing considers the problem to acquire and recover a sparse signal from its linear measurements. In this paper, we propose a new support recovery algorithm from noisy measurements based on the linear programming (LP). LP is widely used to estimate sparse signals, however, we focus on the problem to recover the support of sparse signals rather than the problem to estimate sparse signals themselves. First, we derive an integer linear programming (ILP) formulation for the support recovery problem. Then we obtain the LP based support recovery algorithm by relaxing the ILP. The proposed LP based recovery algorithm has an attracting property that the output of the algorithm is guaranteed to be the maximum a posteiori (MAP) estimate when it is integer valued. We compare the performance of the proposed algorithm to a state-of-the-art algorithm named sparse matching pursuit (SMP) via numerical simulations.

Original languageEnglish
Title of host publicationProceedings of 2016 International Symposium on Information Theory and Its Applications, ISITA 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages270-274
Number of pages5
ISBN (Electronic)9784885523090
Publication statusPublished - 2017 Feb 2
Event3rd International Symposium on Information Theory and Its Applications, ISITA 2016 - Monterey, United States
Duration: 2016 Oct 302016 Nov 2

Other

Other3rd International Symposium on Information Theory and Its Applications, ISITA 2016
CountryUnited States
CityMonterey
Period16/10/3016/11/2

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Information Systems
  • Signal Processing
  • Library and Information Sciences

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    Horii, S., Matsushima, T., & Hirasawa, S. (2017). A note on support recovery of sparse signals using linear programming. In Proceedings of 2016 International Symposium on Information Theory and Its Applications, ISITA 2016 (pp. 270-274). [7840428] Institute of Electrical and Electronics Engineers Inc..