Title
Numerical methods for differential linear matrix equations via Krylov subspace methods.
Abstract
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.
Year
DOI
Venue
2020
10.1016/j.cam.2019.112674
Journal of Computational and Applied Mathematics
Keywords
Field
DocType
65F10
Rank (linear algebra),Krylov subspace,Mathematical analysis,Galerkin method,Linear matrix,Numerical analysis,Sylvester matrix,Lyapunov matrix,Mathematics
Journal
Volume
ISSN
Citations 
370
0377-0427
0
PageRank 
References 
Authors
0.34
1
2
Name
Order
Citations
PageRank
M. Hached122.10
Khalide Jbilou23812.08