Open AccessA note on orthogonal matching pursuit under restricted isometry property
Author(s) -
Chen Xueping,
Liu Jianzhong,
Ding Xianwen,
Huang Hengzhen
Publication year - 2022
Publication title -
iet signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.384
H-Index - 42
eISSN - 1751-9683
pISSN - 1751-9675
DOI - 10.1049/sil2.12096
Subject(s) - matching pursuit , restricted isometry property , isometry (riemannian geometry) , compressed sensing , property (philosophy) , algorithm , signal (programming language) , greedy algorithm , computer science , basis pursuit , mathematics , signal processing , matching (statistics) , noise (video) , mathematical optimization , artificial intelligence , image (mathematics) , statistics , telecommunications , philosophy , radar , epistemology , pure mathematics , programming language
Abstract The orthogonal matching pursuit (OMP) algorithm is a classical greedy algorithm widely used in compressed sensing. The number of iterations required for the OMP algorithm to perform exact the recovery of sparse signals is a fundamental problem in signal processing. In this work, by investigating the relationship between the iteration number for OMP and the signal estimation error based on the restricted isometry property, the authors obtained tighter bounds on the number of iterations required to approximately recover a sparse signal with noise and exact support recovering for the noiseless cases of OMP.