Optimal incorporation of sparsity information by weighted ℓ<inf>1</inf> optimization
説明
Compressed sensing of sparse sources can be improved by incorporating prior knowledge of the source. In this paper we demonstrate a method for optimal selection of weights in weighted $L_1$ norm minimization for a noiseless reconstruction model, and show the improvements in compression that can be achieved.
5 pages, 2 figures, to appear in Proceedings of ISIT2010
収録刊行物
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- 2010 IEEE International Symposium on Information Theory
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2010 IEEE International Symposium on Information Theory 1598-1602, 2010-06-01
IEEE