A note on guaranteed sparse recovery via l1-minimization

被引:107
作者
Foucart, Simon [1 ]
机构
[1] Univ Paris 06, Lab Jacques Louis Lions, Paris, France
关键词
Compressive sensing; Restricted isometry constants; l(1)-minimization;
D O I
10.1016/j.acha.2009.10.004
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
It is proved that every s-sparse vector X is an element of C-N can be recovered from the measurement vector y = Ax is an element of C-m via l(1)-minimization as soon as the 2s-th restricted isometry constant of the matrix A is smaller than 3/(4+root 6) approximate to 0.4652, or smaller than 47(6+root 6) approximate to 0.4734 for large values of s. (C) 2009 Elsevier Inc. All rights reserved.
引用
收藏
页码:97 / 103
页数:7
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