A GAMP-Based Low Complexity Sparse Bayesian Learning Algorithm
Published in IEEE Transactions on Signal Processing • Oct 19, 2017
NobleIDNI6P77W48R07S45
Authors:,,
Maher Al-Shoukairi
Philip Schniter
Bhaskar D. Rao
Abstract
In this paper, we present an algorithm for the sparse signal recovery problem that incorporates damped Gaussian generalized approximate message passing (GGAMP) into expectation-maximization-based sparse Bayesian learning (SBL). In particular, GGAMP is used to implement the E-step in SBL in place of ...
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