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New Bounds for Restricted Isometry Constants

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3 Author(s)
Cai, T.T. ; Dept. of Stat., Univ. of Pennsylvania, Philadelphia, PA, USA ; Lie Wang ; Guangwu Xu

This paper discusses new bounds for restricted isometry constants in compressed sensing. Let Φ be an n × p real matrix and A; be a positive integer with k ≤ n. One of the main results of this paper shows that if the restricted isometry constant δk of Φ satisfies δk <; 0.307 then k-sparse signals are guaranteed to be recovered exactly via ℓ1 minimization when no noise is present and k-sparse signals can be estimated stably in the noisy case. It is also shown that the bound cannot be substantially improved. An explicit example is constructed in which δk = k-1/2k-1 <; 0.5, but it is impossible to recover certain k-sparse signals.

Published in:

Information Theory, IEEE Transactions on  (Volume:56 ,  Issue: 9 )

Date of Publication:

Sept. 2010

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