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Information-theoretic limits on sparse signal recovery: Dense versus sparse measurement matrices
[article]
2008
arXiv
pre-print
We study the information-theoretic limits of exactly recovering the support of a sparse signal using noisy projections defined by various classes of measurement matrices. Our analysis is high-dimensional in nature, in which the number of observations n, the ambient signal dimension p, and the signal sparsity k are all allowed to tend to infinity in a general manner. This paper makes two novel contributions. First, we provide sharper necessary conditions for exact support recovery using general
arXiv:0806.0604v1
fatcat:kpb62qx6qrat5l4cjv2ki4uxvq