4.5 Article

Iterative least-squares solutions of coupled Sylvester matrix equations

期刊

SYSTEMS & CONTROL LETTERS
卷 54, 期 2, 页码 95-107

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.sysconle.2004.06.008

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

向作者/读者索取更多资源

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.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.5
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据