An empirical-bayes approach to recovering linearly constrained non-negative sparse signals

IEEE Transactions on Signal Processing

Volumn 62, Issue 18, 2014, Pages 4689-4703

  Vila, Jeremy P ^a   Schniter, Philip ^a  

^a The Ohio State University   (United States)

Author keywords

Belief propagation; compressed sensing; estimation; expectation maximization algorithms

Indexed keywords

COMPRESSED SENSING; ESTIMATION; FINANCIAL DATA PROCESSING; MAXIMUM PRINCIPLE; NUMERICAL METHODS; SPECTROSCOPY;

BELIEF PROPAGATION; EXPECTATION-MAXIMIZATION ALGORITHMS; HYPERSPECTRAL IMAGING; LINEAR EQUALITY CONSTRAINTS; PORTFOLIO OPTIMIZATION; REGULARIZATION PARAMETERS; STATE-OF-THE-ART PERFORMANCE; STATISTICAL PARAMETERS;

ALGORITHMS;

EID: 84906489211     PISSN: 1053587X     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSP.2014.2337841     Document Type: Article

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