Optimal incorporation of sparsity information by weighted $\ell_1$ optimization
Information Theory
2013-09-17 v2 math.IT
Abstract
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 norm minimization for a noiseless reconstruction model, and show the improvements in compression that can be achieved.
Keywords
Cite
@article{arxiv.1001.1873,
title = {Optimal incorporation of sparsity information by weighted $\ell_1$ optimization},
author = {Toshiyuki Tanaka and Jack Raymond},
journal= {arXiv preprint arXiv:1001.1873},
year = {2013}
}
Comments
5 pages, 2 figures, to appear in Proceedings of ISIT2010