A note on support recovery of sparse signals using linear programming

研究成果: Conference contribution

抄録

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.

本文言語English
ホスト出版物のタイトルProceedings of 2016 International Symposium on Information Theory and Its Applications, ISITA 2016
出版社Institute of Electrical and Electronics Engineers Inc.
ページ270-274
ページ数5
ISBN(電子版)9784885523090
出版ステータスPublished - 2017 2 2
イベント3rd International Symposium on Information Theory and Its Applications, ISITA 2016 - Monterey, United States
継続期間: 2016 10 302016 11 2

Other

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

ASJC Scopus subject areas

  • コンピュータ ネットワークおよび通信
  • ハードウェアとアーキテクチャ
  • 情報システム
  • 信号処理
  • 図書館情報学

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