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A new result on recovery sparse signals using orthogonal matching pursuit

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  • Xueping Chen
  • Jianzhong Liu
  • Jiandong Chen

Abstract

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.

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  • Xueping Chen & Jianzhong Liu & Jiandong Chen, 2022. "A new result on recovery sparse signals using orthogonal matching pursuit," Statistical Theory and Related Fields, Taylor & Francis Journals, vol. 6(3), pages 220-226, August.
    • Handle: RePEc:taf:tstfxx:v:6:y:2022:i:3:p:220-226
    DOI: 10.1080/24754269.2022.2048445
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    Cited by:

    1. Yunzhi Zhang & Xiaotian Guo & Jianzhong Liu & Xueping Chen, 2024. "Generalizations of the Kantorovich and Wielandt Inequalities with Applications to Statistics," Mathematics, MDPI, vol. 12(18), pages 1-13, September.

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