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  4. Modified error bounds for approximate solutions of dense linear systems
 
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Modified error bounds for approximate solutions of dense linear systems

Publikationstyp
Journal Article
Date Issued
2020-05-01
Sprache
English
Author(s)
Minamihata, Atsushi  
Ogita, Takeshi  
Rump, Siegfried M.  orcid-logo
Oishi, Shin’ichi  
Institut
Zuverlässiges Rechnen E-19  
TORE-URI
http://hdl.handle.net/11420/4117
Journal
Journal of computational and applied mathematics  
Volume
369
Article Number
112546
Citation
Journal of Computational and Applied Mathematics (369): 112546 (2020-05-01)
Publisher DOI
10.1016/j.cam.2019.112546
Scopus ID
2-s2.0-85075973812
We derive verified error bounds for approximate solutions of dense linear systems. There are verification methods using an approximate inverse of a coefficient matrix as a preconditioner, where the preconditioned coefficient matrix is likely to be anH-matrix (also known as a generalized diagonally dominant matrix). We focus on two inclusion methods of matrix multiplication for the preconditioning and propose verified error bounds adapted to the inclusion methods. These proposed error bounds are tighter than conventional ones, especially in critically ill-conditioned cases. Numerical results are presented showing the effectiveness of the proposed error bounds.
Subjects
Error bound
H-matrix
Linear system
Verified solution
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