A New Analysis for Support Performance with Block Generalized Orthogonal Matching Pursuit | Zendy

Chaoyu Xia | Zendy; Zhengchun Zhou | Zendy; Chun-Bo Guo | Zendy; Yuhan Hao | Zendy; Chen Hou | Zendy

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A New Analysis for Support Performance with Block Generalized Orthogonal Matching Pursuit

Author(s) -

Chaoyu Xia,

Zhengchun Zhou,

Chun-Bo Guo,

Yuhan Hao,

Chen Hou

Publication year - 2021

Publication title -

mathematical problems in engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.262

H-Index - 62

eISSN - 1026-7077

pISSN - 1024-123X

DOI - 10.1155/2021/9438793

Subject(s) - matching pursuit , block (permutation group theory) , restricted isometry property , compressed sensing , matching (statistics) , isometry (riemannian geometry) , algorithm , mathematics , property (philosophy) , computer science , combinatorics , pure mathematics , statistics , philosophy , epistemology

For recovering block-sparse signals with unknown block structures using compressive sensing, a block orthogonal matching pursuit- (BOMP-) like block generalized orthogonal matching pursuit (BgOMP) algorithm has been proposed recently. This paper focuses on support conditions of recovery of any - sparse block signals incorporating BgOMP under the framework of restricted isometry property (RIP). The proposed support conditions guarantee that BgOMP can achieve accurate recovery block-sparse signals within iterations.

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