Iterative least-squares solutions of coupled Sylvester matrix equations

被引:365
作者
Ding, F
Chen, TW [1 ]
机构
[1] Univ Alberta, Dept Elect & Comp Engn, Edmonton, AB T6G 2V4, Canada
[2] Univ Alberta, Edmonton, AB, Canada
基金
中国国家自然科学基金; 加拿大自然科学与工程研究理事会;
关键词
Sylvester matrix equation; Lyapunov matrix equation; identification; estimation; least squares; Jacobi iteration; Gauss-Seidel iteration; Hadamard product; star product; hierarchical identification principle;
D O I
10.1016/j.sysconle.2004.06.008
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, we present a general family of iterative methods to solve linear equations, which includes the well-known Jacobi and Gauss-Seidel iterations as its special cases. The methods are extended to solve coupled Sylvester matrix equations. In our approach, we regard the unknown matrices to be solved as the system parameters to be identified, and propose a least-squares iterative algorithm by applying a hierarchical identification principle and by introducing the block-matrix inner product (the star product for short). We prove that the iterative solution consistently converges to the exact solution for any initial value. The algorithms proposed require less storage capacity than the existing numerical ones. Finally, the algorithms are tested on computer and the results verify the theoretical findings. (C) 2004 Elsevier B.V. All rights reserved.
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页码:95 / 107
页数:13
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