Almost sure localization of the eigenvalues in a Gaussian information plus noise model - Application to the spiked models

被引:41
作者
Loubaton, Philippe [1 ]
Vallet, Pascal [1 ]
机构
[1] Univ Paris Est Marne la Vallee, LIGM CNRS UMR 8049, F-77454 Marne La Vallee, France
关键词
random matrix theory; gaussian information plus noise model; localization of the eigenvalues; spiked models; LIMITING SPECTRAL DISTRIBUTION; COVARIANCE MATRICES; FUNCTIONALS;
D O I
10.1214/EJP.v16-943
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Let Sigma(N) be a M x N random matrix defined by Sigma(N) = B-N + sigma W-N where B-N is a uniformly bounded deterministic matrix and where W-N is an independent identically distributed complex Gaussian matrix with zero mean and variance 1/N entries. The purpose of this paper is to study the almost sure location of the eigenvalues (lambda) over cap (1,N) >= ... >= (lambda) over cap (M,N) of the Gram matrix Sigma(N)Sigma(N)* when M and N converge to +infinity such that the ratio c(N) = M/N converges towards a constant c > 0. The results are used in order to derive, using an alternative approach, known results concerning the behaviour of the largest eigenvalues of Sigma(N)Sigma(N)* when the rank of B-N remains fixed and M, N tend to +infinity.
引用
收藏
页码:1934 / 1959
页数:26
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