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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Vydané v:	IEEE transactions on signal processing Ročník 63; číslo 21; s. 5868 - 5877
Hlavný autor:	Wang, Jian
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	IEEE 01.11.2015
Predmet:	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
On-line prístup:	Získať plný text
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