Gradient based and least squares based iterative algorithms for matrix equations AXB plus CXTD = F

被引:171
作者
Xie, Li [1 ]
Liu, Yanjun [1 ]
Yang, Huizhong [1 ]
机构
[1] Jiangnan Univ, Control Sci & Engn Res Ctr, Wuxi 214122, Peoples R China
基金
中国国家自然科学基金;
关键词
Iterative algorithm; Gradient search; Least squares; Lyapunov matrix equations; Sylvester matrix equations; AUXILIARY MODEL; IDENTIFICATION METHODS; PARAMETER-ESTIMATION; PERFORMANCE ANALYSIS;
D O I
10.1016/j.amc.2010.07.019
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
This paper develops a gradient based and a least squares based iterative algorithms for solving matrix equation AXB + (CXD)-D-T = F. The basic idea is to decompose the matrix equation (system) under consideration into two subsystems by applying the hierarchical identification principle and to derive the iterative algorithms by extending the iterative methods for solving Ax = b and AXB = F. The analysis shows that when the matrix equation has a unique solution (under the sense of least squares), the iterative solution converges to the exact solution for any initial values. A numerical example verifies the proposed theorems. (C) 2010 Elsevier Inc. All rights reserved.
引用
收藏
页码:2191 / 2199
页数:9
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