Uniform Uncertainty Principle for Bernoulli and Subgaussian Ensembles

被引:190
作者
Mendelson, Shahar [2 ,3 ]
Pajor, Alain [1 ]
Tomczak-Jaegermann, Nicole [4 ]
机构
[1] Univ Paris Est, Lab Anal & Math Appl, F-77454 Champs Sur Marne 2, Marne La Vallee, France
[2] Australian Natl Univ, Ctr Math & Its Applicat, Canberra, ACT 0200, Australia
[3] Technion Israel Inst Technol, Dept Math, IL-32000 Haifa, Israel
[4] Univ Alberta, Dept Math & Stat Sci, Edmonton, AB T6G 2G1, Canada
基金
以色列科学基金会; 澳大利亚研究理事会;
关键词
Uniform uncertainty principle; Approximate reconstruction; Random matrices; Generic chaining; 46B07; 41A45; 94B75; 52B05; 62G99;
D O I
10.1007/s00365-007-9005-8
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
The paper considers random matrices with independent subgaussian columns and provides a new elementary proof of the Uniform Uncertainty Principle for such matrices. The Principle was introduced by Candes, Romberg and Tao in 2004; for subgaussian random matrices it was carlier proved by the present authors, as a consequence of a general result based on a generic chaining method of Talagrand. The present proof combines a simple measure concentration and a covering argument, which are standard tools of high-dimensional convexity.
引用
收藏
页码:277 / 289
页数:13
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