Preconditioners for the conjugate gradient algorithm using Gram-Schmidt and least squares methods
Date issued
January 2007
In
INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS
Vol
1
No
84
From page
89
To page
108
Reviewed by peer
1
Subjects
Conjugate gradient method Preconditioner Gram–Schmidt orthogonalization Least squares Condition number
Abstract
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.
Publication type
journal article