Monotone convergence of Newton-like iteration for a structured nonlinear eigen-problem

被引：0

作者：

Guo, Pei -Chang ^{[1
]}

Gao, Shi-Chen ^{[1
]}

Yang, Yong-Qing ^{[1
]}

机构：

[1] China Univ Geosci, Sch Sci, Beijing 100083, Peoples R China

来源：

APPLIED MATHEMATICS AND COMPUTATION | 2023年 / 437卷

基金：

中国国家自然科学基金;

关键词：

Eigen-problem; Stieltjes matrix; Newton -like method; Monotone convergence;

D O I：

10.1016/j.amc.2022.127532

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

A structured eigen-problem Ax +F(x) = lambda x is studied in this paper, where in applications A is an element of R-nxn is an irreducible Stieltjes matrix. Under certain restrictions, this problem has a unique positive solution. We show that, starting from a multiple of the positive eigenvec-tor of A , the Newton-like algorithm for this eigen-problem is well defined and converges monotonically. Numerical results illustrate the effectiveness of this Newton-like method. (C) 2022 Elsevier Inc. All rights reserved.

引用

页数：7

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