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This work discusses the problem of sparse signal recovery when there iscorrelation among the values of non-zero entries. We examine intra-vectorcorrelation in the context of the block sparse model and inter-vectorcorrelation in the context of the multiple measurement vector model, as well astheir combination. Algorithms based on the sparse Bayesian learning arepresented and the benefits of incorporating correlation at the algorithm levelare discussed. The impact of correlation on the limits of support recovery isalso discussed highlighting the different impact intra-vector and inter-vectorcorrelations have on such limits.

Sparse Signal Recovery in the Presence of Intra-Vector and Inter-Vector Correlation