On the interval of fluctuation of the singular values of random matrices

被引:10
作者
Guedon, Olivier [1 ]
Litvak, Alexander E. [2 ]
Pajor, Alain [1 ]
Tomczak-Jaegermann, Nicole [2 ]
机构
[1] Univ Paris Est, Lab Anal & Math Appl, UMR 8050, F-77454 Marne La Vallee, France
[2] Univ Alberta, Dept Math & Stat Sci, Edmonton, AB T6G 2G1, Canada
关键词
Random matrices; norm of random matrices; approximation of covariance matrices; compressed sensing; restricted isometry property; log-concave random vectors; concentration inequalities; deviation inequalities; heavy tails; spectrum; singular values; order statistics; LARGEST EIGENVALUE; LIMIT; RECOVERY;
D O I
10.4171/JEMS/697
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Let A be a matrix whose columns X-1, . . . , X-N are independent random vectors in R n. Assume that the tails of the 1-dimensional marginals decay as P(vertical bar < X-i ,a >vertical bar >= t) <= t(-p) uniformly in a is an element of Sn-1 and i <= N. Then for p > 4 we prove that with high probability A/root n has the Restricted Isometry Property (RIP) provided that the Euclidean norms vertical bar X-i vertical bar are concentrated around root n. We also show that the covariance matrix is well approximated by empirical covariance matrices and establish corresponding quantitative estimates on the rate of convergence in terms of the ratio n/N. Moreover, we obtain sharp bounds for both problems when the decay is of the type exp (-t(alpha)) with alpha is an element of[0,2], extending the known case alpha is an element of[1,2].
引用
收藏
页码:1469 / 1505
页数:37
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