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Licensed Unlicensed Requires Authentication Published by De Gruyter August 13, 2015

The restricted isometry property for random matrices with ϕ-subgaussian entries

  • Yuriy Kozachenko and Viktor Troshki EMAIL logo

Abstract

The aim of this article is to construct the generalized random matrices, which satisfies the restricted isometry property (as introduced by Candes and Tao). Let the data be presented as a product of a vector with not more than K nonzero coordinates by a given matrix. We show that for such data we can change the upper bound of the variable K. In particular, we prove that the random matrices whose entries are independent realizations of random variables from ϕ-subgaussian space could be used in the theory of compressive sensing for encoding vectors.

Received: 2014-10-18
Accepted: 2015-2-20
Published Online: 2015-8-13
Published in Print: 2015-9-1

© 2015 by De Gruyter

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