Bayesian Hypothesis Testing for Block Sparse Signal Recovery
Machine Learning
2015-08-25 v1 Information Theory
math.IT
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.
Keywords
Cite
@article{arxiv.1508.05495,
title = {Bayesian Hypothesis Testing for Block Sparse Signal Recovery},
author = {Mehdi Korki and Hadi Zayyani and Jingxin Zhang},
journal= {arXiv preprint arXiv:1508.05495},
year = {2015}
}
Comments
5 pages, 2 figures. arXiv admin note: text overlap with arXiv:1412.2316