Bayesian Hypothesis Testing for Block Sparse Signal Recovery
Abstract
This letter presents a novel Block Bayesian Hypothesis Testing Algorithm (Block-BHTA) for reconstructing block sparse signals with unknown block structures. The Block-BHTA comprises the detection and recovery of the supports, and the estimation of the amplitudes of the block sparse signal. The support detection and recovery is performed using a Bayesian hypothesis testing. Then, based on the detected and reconstructed supports, the nonzero amplitudes are estimated by linear MMSE. The effectiveness of Block-BHTA is demonstrated by numerical experiments.
- Publication:
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arXiv e-prints
- Pub Date:
- August 2015
- DOI:
- 10.48550/arXiv.1508.05495
- arXiv:
- arXiv:1508.05495
- Bibcode:
- 2015arXiv150805495K
- Keywords:
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- Statistics - Machine Learning;
- Computer Science - Information Theory
- E-Print:
- 5 pages, 2 figures. arXiv admin note: text overlap with arXiv:1412.2316