Expectation-Maximization Gaussian-Mixture Approximate Message Passing
Volume: 61, Issue: 19, Pages: 4658 - 4672
Published: Oct 1, 2013
Abstract
When recovering a sparse signal from noisy compressive linear measurements, the distribution of the signal's non-zero coefficients can have a profound effect on recovery mean-squared error (MSE). If this distribution was apriori known, then one could use computationally efficient approximate message passing (AMP) techniques for nearly minimum MSE (MMSE) recovery. In practice, though, the distribution is unknown, motivating the use of robust...
Paper Details
Title
Expectation-Maximization Gaussian-Mixture Approximate Message Passing
Published Date
Oct 1, 2013
Volume
61
Issue
19
Pages
4658 - 4672
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