Paper Info
Title
Randomized simultaneous orthogonal matching pursuit
Abstract
In this paper, we develop randomized simultaneous orthogonal matching pursuit (RandSOMP) algorithm which computes an approximation of the Bayesian minimum mean squared error (MMSE) estimate of an unknown rowsparse signal matrix. The approximation is based on greedy iterations, as in SOMP, and it elegantly incorporates the prior knowledge of the probability distribution of the signal and noise matrices into the estimation process. Unlike the exact MMSE estimator which is computationally intractable to solve, the Bayesian greedy pursuit approach offers a computationally feasible way to approximate the MMSE estimate. Our simulations illustrate that the proposed RandSOMP algorithm outperforms SOMP both in terms of mean-squared error and probability of exact support recovery. The benefits of RandSOMP arc further illustrated in direction-of-arrival estimation with sensor arrays and image denoising.
Year
Venue
Keywords
2015
European Signal Processing Conference
Bayes,minimum mean-squared error (MMSE),multichannel sparse recovery,compressed sensing
DocType
ISSN
Citations 
Conference
2076-1465
0
PageRank 
References 
Authors
0.34
6
3
Name
Order
Citations
PageRank
Aqib Ejaz100.34
Esa Ollila235133.51
Visa Koivunen31917187.81