A self-adaptive trust region method for extreme B-eigenvalues of symmetric tensors

被引：0
|
作者：
Cao, Mingyuan [1 ]
Huang, Qingdao [1 ]
Yang, Yueting [2 ]
机构：
[1] Jilin Univ, Coll Math, 2699 Qianjin St, Changchun 130000, Jilin, Peoples R China
[2] Beihua Univ, Coll Math & Stat, Jilin 132013, Jilin, Peoples R China
来源：
NUMERICAL ALGORITHMS | 2019年 / 81卷 / 02期
基金：
中国国家自然科学基金;
关键词：
Symmetric tensors; Eigenvalues of tensors; Polynomial optimization; Trust region method; Global convergence;
D O I：
10.1007/s11075-018-0554-7
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
A self-adaptive trust region method is presented for finding the largest or smallest B-eigenvalues of symmetric tensors. One of the important features of this method is that B-eigenvalues problem of symmetric tensors is transformed into a homogenous polynomial optimization. Global convergence of the proposed algorithm and second-order necessary conditions of the optimal solutions are established, respectively. Numerical experiments are listed to illustrate the efficiency of the proposed method.
引用
收藏
页码：407 / 420
页数：14
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