Repository logo

Infoscience

  • English
  • French
Log In
Logo EPFL, École polytechnique fédérale de Lausanne

Infoscience

  • English
  • French
Log In
  1. Home
  2. Academic and Research Output
  3. Journal articles
  4. Projection Methods For Large-Scale T-Sylvester Equations
 
research article

Projection Methods For Large-Scale T-Sylvester Equations

Dopico, Froilan M.
•
Gonzalez, Javier
•
Kressner, Daniel  
Show more
2016
Mathematics Of Computation

The matrix Sylvester equation for congruence, or T-Sylvester equation, has recently attracted considerable attention as a consequence of its close relation to palindromic eigenvalue problems. The theory concerning T-Sylvester equations is rather well understood, and there are stable and efficient numerical algorithms which solve these equations for small- to medium-sized matrices. However, developing numerical algorithms for solving large-scale T-Sylvester equations still remains an open problem. In this paper, we present several projection algorithms based on different Krylov spaces for solving this problem when the right-hand side of the T-Sylvester equation is a low-rank matrix. The new algorithms have been extensively tested, and the reported numerical results show that they work very well in practice, offering clear guidance on which algorithm is the most convenient in each situation.

  • Details
  • Metrics
Type
research article
DOI
10.1090/mcom/3081
Web of Science ID

WOS:000379063300013

Author(s)
Dopico, Froilan M.
Gonzalez, Javier
Kressner, Daniel  
Simoncini, Valeria
Date Issued

2016

Publisher

Amer Mathematical Soc

Published in
Mathematics Of Computation
Volume

85

Issue

1

Start page

2427

End page

2455

Subjects

Matrix equations

•

Krylov subspace

•

iterative methods

•

large-scale equations

•

Sylvester equation

•

Sylvester equation for congruence

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
ANCHP  
Available on Infoscience
October 18, 2016
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/130294
Logo EPFL, École polytechnique fédérale de Lausanne
  • Contact
  • infoscience@epfl.ch

  • Follow us on Facebook
  • Follow us on Instagram
  • Follow us on LinkedIn
  • Follow us on X
  • Follow us on Youtube
AccessibilityLegal noticePrivacy policyCookie settingsEnd User AgreementGet helpFeedback

Infoscience is a service managed and provided by the Library and IT Services of EPFL. © EPFL, tous droits réservés