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Support Recovery from Noisy Measurement via Orthogonal Multi-Matching Pursuit

Published online by Cambridge University Press:  24 May 2016

Wei Dan
Wei Dan*
Affiliation:
School of Mathematics and Statistics, Guangdong University of Finance & Economics, Guangzhou 510320, China
*
*Corresponding author. Email address: wdan@gdufe.edu.cn (W. Dan)
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Abstract

In this paper, a new stopping rule is proposed for orthogonal multi-matching pursuit (OMMP). We show that, for ℓ2 bounded noise case, OMMP with the new stopping rule can recover the true support of any K-sparse signal x from noisy measurements y = Фx + 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.

Keywords

65D1565J2268W40sparse recoveryorthogonal matching pursuitrestricted isometry property
Type
Research Article
Information
Numerical Mathematics: Theory, Methods and Applications , Volume 9 , Issue 2 , May 2016 , pp. 185 - 192
Copyright
Copyright © Global-Science Press 2016 

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