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Preconditioners for the conjugate gradient algorithm using Gram-Schmidt and least squares methods
Date de parution
2007-1
In
INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS
Vol.
1
No
84
De la page
89
A la page
108
Revu par les pairs
1
Résumé
This paper is devoted to the study of some preconditioners for the conjugate gradient algorithm used to solve large sparse linear and symmetric positive definite systems. The construction of a preconditioner based on the Gram-Schmidt orthogonalization process and the least squares method is presented. Some results on the condition number of the preconditioned system are provided. Finally, numerical comparisons are given for different preconditioners.
Identifiants
Type de publication
journal article
