Support Recovery With Orthogonal Matching Pursuit in the Presence of Noise

Support recovery of sparse signals from compressed linear measurements is a fundamental problem in compressed sensing (CS). In this article, we study the orthogonal matching pursuit (OMP) algorithm for the recovery of support under noise. We consider two signal-to-noise ratio (SNR) settings: 1) the...

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Bibliographic Details
Published in:	IEEE transactions on signal processing Vol. 63; no. 21; pp. 5868 - 5877
Main Author:	Wang, Jian
Format:	Journal Article
Language:	English
Published:	IEEE 01.11.2015
Subjects:	Algorithms Compressed sensing Compressed sensing (CS) Constants Error analysis Matching Matching pursuit algorithms minimum-to-average ratio (MAR) Noise Noise measurement orthogonal matching pursuit (OMP) Recovery restricted isometry property (RIP) Signal processing algorithms Signal to noise ratio signal-to-noise ratio (SNR) Sparse matrices Transaction processing
ISSN:	1053-587X, 1941-0476
Online Access:	Get full text
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