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Sparse Bayesian Learning (SBL) has been used as a sparse signal recovery algorithm for compressed sensing. It has been shown that SBL is easy to use and can recover sparse signals more accurately than the l1 based optimization approaches, which require a delicate choice of user parameters. We propose herein a modified Expectation Maximization (EM) based SBL algorithm referred to as SBL-alpha and...
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