Convergence and Stability of a Class of Iteratively Re-weighted Least Squares Algorithms for Sparse Signal Recovery in the Presence of Noise

In this paper, we study the theoretical properties of a class of iteratively re-weighted least squares (IRLS) algorithms for sparse signal recovery in the presence of noise. We demonstrate a one-to-one correspondence between this class of algorithms and a class of Expectation-Maximization (EM) algor...

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Bibliographic Details

Published in:	IEEE transactions on signal processing Vol. 62; no. 1; pp. 183 - 195
Main Authors:	Babadi, Behtash, Ba, Demba, Purdon, Patrick L, Brown, Emery N
Format:	Journal Article
Language:	English
Published:	United States 30.10.2013
ISSN:	1053-587X
Online Access:	Get full text
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