Convergence and Stability 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 iteratively re-weighted least squares (IRLS) algorithms and their utility in sparse signal recovery in the presence of noise. We demonstrate a one-to-one correspondence between the IRLS algorithms and a class of Expectation-Maximization (EM) algo...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Institute of Electrical and Electronics Engineers (IEEE)
2014
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| Online Access: | http://hdl.handle.net/1721.1/86328 https://orcid.org/0000-0001-5651-5060 https://orcid.org/0000-0003-2668-7819 |