Options
Preconditioners for the conjugate gradient algorithm using Gram–Schmidt and least squares methods
In
International Journal of Computer Mathematics, 2007/84/1/89-108
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
