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论文类型：期刊论文

发表时间：2021-05-04

发表刊物：COMMUNICATIONS IN STATISTICS-THEORY AND METHODS

卷号：50

期号：10

页面范围：2419-2428

ISSN号：0361-0926

关键字：random matrix; folded Gaussian distribution; tail bound; the largest singular value; expectation bound

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.