A likelihood based method for compressive signal recovery under Gaussian and saturation noise
Author:
Publisher
Elsevier BV
Subject
Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software,Control and Systems Engineering
Reference30 articles.
1. An introduction to compressive sampling;Candes;IEEE Signal Process. Mag.,2008
2. Statistical Learning with Sparsity: The Lasso and Generalizations;Hastie,2015
3. The restricted isometry property and its implications for compressed sensing;Candes;C. R. Math.,2008
4. A fast iterative shrinkage-thresholding algorithm for linear inverse problems;Beck;SIAM J. Imaging Sci.,2009
5. New method of sparse parameter estimation in separable models and its use for spectral analysis of irregularly sampled data;Stoica;IEEE Trans. Signal Process.,2010
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