Dimension-free bounds for largest singular values of matrix Gaussian series

被引：1
|
作者：
Gao, Xianjie [1 ]
Zhang, Chao [1 ]
Zhang, Hongwei [1 ]
机构：
[1] Dalian Univ Technol, Sch Math Sci, Dalian, Liaoning, Peoples R China
来源：
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2021年 / 50卷 / 10期
基金：
中国国家自然科学基金;
关键词：
random matrix; folded Gaussian distribution; tail bound; the largest singular value; expectation bound;
D O I：
10.1080/03610926.2019.1670846
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：
The matrix Gaussian series refers to a sum of fixed matrices weighted by independent standard normal variables and plays an important in various fields related to probability theory. In this paper, we present the dimension-free tail bounds and expectation bounds for the largest singular value (LSV) of matrix Gaussian series, respectively. By using the resulting bounds, we compute the expectation bounds for LSVs of Gaussian Wigner matrix and Gaussian Toeplitz matrix, respectively.
引用
收藏
页码：2419 / 2428
页数：10
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