Singular value decomposition of time-varying matrices

被引：20

作者：

Baumann, M ^{[1
]}

Helmke, U ^{[1
]}

机构：

[1] Univ Wurzburg, Inst Math, D-97074 Wurzburg, Germany

来源：

FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE | 2003年 / 19卷 / 03期

关键词：

singular value decomposition; time-varying matrices; continuation methods;

D O I：

10.1016/S0167-739X(02)00162-0

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

This paper is concerned with an algorithm to compute the singular value decomposition (SVD) of time-varying square matrices. In a first step we consider the task of diagonalizing symmetric time-varying matrices A(t). A differential equation is proposed, whose solutions asymptotically track the diagonalizing transformation. In particular, perfect matching of the initial conditions is not required and the solutions converge exponentially towards the desired transformation. Then the desired differential equation for tracking the SVD is derived. Robustness of the algorithms is guaranteed by our approach. (C) 2002 Elsevier Science B.V. All rights reserved.

引用

页码：353 / 361

页数：9

共 11 条

[1]

ABRAHAM R, 1988, TENSOR ANAL APPL

[2]

BELL SJG, 1994, NUMER ANAL REP, V2

[3] The equations ATX±XTA=B [J].