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THE PERFORMANCE OF ORTHOGONAL MULTI-MATCHING PURSUIT UNDER THE RESTRICTED ISOMETRY PROPERTY 被引量:2

THE PERFORMANCE OF ORTHOGONAL MULTI-MATCHING PURSUIT UNDER THE RESTRICTED ISOMETRY PROPERTY
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摘要 The orthogonal multi-matching pursuit (OMMP) is a natural extension of the orthogo- nal matching pursuit (OMP). We denote the OMMP with the parameter M as OMMP(M) where M ≥ 1 is an integer. The main difference between OMP and OMMP(M) is that OMMP(M) selects M atoms per iteration, while OMP only adds one atom to the op- timal atom set. In this paper, we study the performance of orthogonal multi-matching pursuit under RIP. In particular, we show that, when the measurement matrix A satisfies (25s, 1/10)-RIP, OMMP(M0) with M0 = 12 can recover s-sparse signals within s itera- tions. We furthermore prove that OMMP(M) can recover s-sparse signals within O(s/M) iterations for a large class of M. The orthogonal multi-matching pursuit (OMMP) is a natural extension of the orthogo- nal matching pursuit (OMP). We denote the OMMP with the parameter M as OMMP(M) where M ≥ 1 is an integer. The main difference between OMP and OMMP(M) is that OMMP(M) selects M atoms per iteration, while OMP only adds one atom to the op- timal atom set. In this paper, we study the performance of orthogonal multi-matching pursuit under RIP. In particular, we show that, when the measurement matrix A satisfies (25s, 1/10)-RIP, OMMP(M0) with M0 = 12 can recover s-sparse signals within s itera- tions. We furthermore prove that OMMP(M) can recover s-sparse signals within O(s/M) iterations for a large class of M.
作者 Zhiqiang Xu
机构地区 LSEC
出处 《Journal of Computational Mathematics》 SCIE CSCD 2015年第5期495-516,共22页 计算数学(英文)
关键词 Sparse signals Compressed sensing Greedy algorithms Sparse signals, Compressed sensing, Greedy algorithms
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