Support Recovery from Noisy Measurement via Orthogonal Multi-Matching Pursuit. Issue 2 (24th May 2016)

• Record Type: Journal Article
• Authors: Dan, Wei
• Is Part Of: Numerical mathematics. Volume 9:Issue 2(2016)
• Page Start: 185
• Page End: 192
• Publication Date: 2016-05-24
• Subjects: 65D15, -- 65J22, -- 68W40; sparse recovery, -- orthogonal matching pursuit, -- restricted isometry property; Numerical analysis -- Periodicals; Numerical analysis; Periodicals; 518.05
• DOI: 10.4208/nmtma.2016.m1424
• Languages: English
• ISSNs: 1004-8979

Abstract

Abstract: In this paper, a new stopping rule is proposed for orthogonal multi-matching pursuit (OMMP). We show that, for ℓ 2 bounded noise case, OMMP with the new stopping rule can recover the true support of any K -sparse signal x from noisy measurements y = Ф x + e in at most K iterations, provided that all the nonzero components of x and the elements of the matrix Ф satisfy certain requirements. The proposed method can improve the existing result. In particular, for the noiseless case, OMMP can exactly recover any K -sparse signal under the same RIP condition.