Numerical methods for differential linear matrix equations via Krylov subspace methods

被引：2

作者：

Hached, M. ^{[1
]}

Jbilou, K. ^{[2
]}

机构：

[1] Univ Lille, UFR Math, Lab P Painleve UMR 8524, IUT A, Rue Rech,BP 179, F-59653 Villeneuve Dascq, France

[2] Univ Littoral Cote dOpale, Lab Math Pures & Appliquees, 50 Rue F Buisson,BP 699, F-62228 Calais, France

来源：

JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS | 2020年 / 370卷

关键词：

Sylvester equation; Lyapunov equation; Global Arnoldi; Matrix Krylov subspace; APPROXIMATIONS; ALGORITHMS;

D O I：

10.1016/j.cam.2019.112674

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In the present paper, we present some numerical methods for computing approximate solutions to some large differential linear matrix equations. In the first part of this work, we deal with differential generalized Sylvester matrix equations with full rank right-hand sides using a global Galerkin and a norm-minimization approaches. In the second part, we consider large differential Lyapunov matrix equations with low rank right-hand sides and use the extended global Arnoldi process to produce low rank approximate solutions. We give some theoretical results and present some numerical examples. (C) 2019 Published by Elsevier B.V.

引用

页数：12

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