Average Performance of Orthogonal Matching Pursuit (OMP) for Sparse Approximation

被引：21

作者：

Schnass, Karin ^{[1
]}

机构：

[1] Univ Innsbruck, Dept Math, A-6020 Innsbruck, Austria

来源：

IEEE SIGNAL PROCESSING LETTERS | 2018年 / 25卷 / 12期

基金：

奥地利科学基金会;

关键词：

Sparse approximation; orthogonal matching pursuit; average case analysis; decaying coefficients; SIGNAL RECOVERY;

D O I：

10.1109/LSP.2018.2878061

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

We present a theoretical analysis of the average performance of orthogonal matching pursuit (OMP) for sparse approximation. For signals that are generated from a dictionary with K atoms and coherence mu and coefficients corresponding to a geometric sequence with parameter alpha < 1, we show that OMP is successful with high probability as long as the sparsity level S scales as S mu(2) log K less than or similar to 1 - alpha. This improves by an order of magnitude over worst case results and shows that OMP and its famous competitor Basis Pursuit outperform each other depending on the setting.

引用

页码：1865 / 1869

页数：5

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