A new result on recovery sparse signals using orthogonal matching pursuit

Orthogonal matching pursuit (OMP) algorithm is a classical greedy algorithm widely used in compressed sensing. In this paper, by exploiting the Wielandt inequality and some properties of orthogonal projection matrix, we obtained a new number of iterations required for the OMP algorithm to perform ex...

Full description

Saved in:
Bibliographic Details
Published inStatistical theory and related fields Vol. 6; no. 3; pp. 220 - 226
Main Authors Chen, Xueping, Liu, Jianzhong, Chen, Jiandong
Format Journal Article
LanguageEnglish
Published Taylor & Francis 26.08.2022
Taylor & Francis Group
Subjects
Compressed sensing
orthogonal matching pursuit
orthogonal projection matrix
Wielandt inequality
Online AccessGet full text

Cover

More Information
Summary:Orthogonal matching pursuit (OMP) algorithm is a classical greedy algorithm widely used in compressed sensing. In this paper, by exploiting the Wielandt inequality and some properties of orthogonal projection matrix, we obtained a new number of iterations required for the OMP algorithm to perform exact recovery of sparse signals, which improves significantly upon the latest results as we know.
ISSN:2475-4269
2475-4277
DOI:10.1080/24754269.2022.2048445