Title

Recovery of sparsest signals via l(q)-minimization

Authors

Authors

Q. Y. Sun

Comments

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Abbreviated Journal Title

Appl. Comput. Harmon. Anal.

Keywords

Compressive sampling; l(q)-minimization; Sparse signal; RECONSTRUCTION; MINIMIZATION; Mathematics, Applied; Physics, Mathematical

Abstract

In this paper, it is proved that every s-sparse vector x is an element of R-n can be exactly recovered from the measurement vector z = Ax is an element of R-m via some l(q)-minimization with 0 < q <= 1, as soon as each s-sparse vector x is an element of R-n is uniquely determined by the measurement z. Moreover it is shown that the exponent q in the l(q)-minimization can be so chosen to be about 0.6796 x (1- delta(25)(A)), where delta(25)(A) is the restricted isometry constant of order 2s for the measurement matrix A. (C) 2011 Elsevier Inc. All rights reserved.

Journal Title

Applied and Computational Harmonic Analysis

Volume

32

Issue/Number

3

Publication Date

1-1-2012

Document Type

Article

Language

English

First Page

329

Last Page

341

WOS Identifier

WOS:000301564900002

ISSN

1063-5203

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