UTAMP-SBL, a sparse Bayesian learning algorithm built on unitary-transformed approximate message passing, recovers sparse signals faster and more robustly than GGAMP-SBL on difficult measurement matrices.
Message-pass ing algo- rithms for compressed sensing,
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Sparse Bayesian Learning Using Approximate Message Passing with Unitary Transformation
UTAMP-SBL, a sparse Bayesian learning algorithm built on unitary-transformed approximate message passing, recovers sparse signals faster and more robustly than GGAMP-SBL on difficult measurement matrices.