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Number of measurements in sparse signal recovery

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3 Author(s)
Tune, P. ; Univ. of Melbourne, Melbourne, VIC, Australia ; Bhaskaran, S.R. ; Hanly, S.

We analyze the asymptotic performance of sparse signal recovery from noisy measurements. In particular, we generalize some of the existing results for the Gaussian case to sub-Gaussian and other ensembles. An achievable result is presented for the linear sparsity regime. A converse on the number of required measurements in the sub-linear regime is also presented, which cover many of the widely used measurement ensembles. Our converse idea makes use of a correspondence between compressed sensing ideas and compound channels in information theory.

Published in:

Information Theory, 2009. ISIT 2009. IEEE International Symposium on

Date of Conference:

June 28 2009-July 3 2009

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