ASYMPTOTIC EIGENVALUE ESTIMATION FOR A CLASS OF STRUCTURED MATRICES

作     者：Juan Liang Jiangzhou Lai Qiang Niu 

作者机构：School of Math.and StatisticsMinnan Normal UniversityZhangzhou 363000FujianPR China School of Math.and Computer ScienceFuzhou UniversityFuzhou 350108FujianPR China Dept.of Mathematical SciencesXi'an Jiaotong-Liverpool UniversitySuzhou 215123JiangsuPR China 

出 版 物：《Annals of Applied Mathematics》 (应用数学年刊（英文版）)

年 卷 期：2019年第35卷第2期

页      面：152-158页

学科分类：07[理学] 070104[理学-应用数学] 0701[理学-数学] 

基　　金：Juan Liang’s work was supported by Young and middle-aged teachers education research project of Fujian Provincial Education Department No.JT180300 Jiangzhou Lai’s work was supported by Core Courses for undergraduate majors of Fuzhou university No.0360-52000732 Qiang Niu’s work was supported by XJTLU research enhancement fund No.REF-18-01-04 and the XJTLU Key Programme Special Fund(KSF) 

主　　题：Toeplitz matrix eigenvalue rank-one modification trace 

摘      要：In this paper we consider eigenvalue asymptotic estimations for a class of structured matrices arising from statistical applications. The asymptotic upper bounds of the largest eigenvalue(λmax) and the sum of squares of eigenvalues(■)are derived. Both these bounds are useful in examining the stability of certain Markov process. Numerical examples are provided to illustrate tightness of the bounds.