It is well known that the convergence of the conjugate gradient method for solving symmetric positive definite linear systems depends to a large extent on the eigenvalue distribution. In many cases, it is observed that “removing ” the extreme eigenvalues can greatly improve the convergence. Several preconditioning techniques based on approximate eigenelements have been proposed in the past few years that attempt to tackle this problem. The proposed approaches can be split into two main families depending on whether the extreme eigenvalues are moved exactly to one or are shift to close to one. The first technique is often referred to the deflating approach, while the latter is referred to as coarse grid preconditioner by analogy to technique...
A preconditioned simultaneous iteration method is described for the solution of the generalized eige...
Recently an efficient method (DACG) for the partial solution of the symmetric generalized eigenprobl...
We consider the problem of solving a symmetric, positive def-inite system of linear equations. The m...
In this paper, the convergence analysis of the conventional conjugate Gradient method was reviewed. ...
The computation of the smallest eigenvalues and eigenvectors of large numerical problems is a very i...
The computation of the smallest eigenvalues and eigenvectors of large numerical problems is a very i...
This article introduces and analyzes a new adaptive algorithm for solving symmetric positive definit...
We exploit an optimization method, called deflation-accelerated conjugate gradient (DACG), which seq...
AbstractThis paper deals with the convergence analysis of various preconditioned iterations to compu...
In this article a new family of preconditioners is introduced for symmetric positive definite linear...
AbstractIterative methods for solving large, sparse, symmetric eigenvalue problems often encounter c...
2In this paper, we present preconditioning techniques to accelerate the convergence of Krylov solve...
To compute the smallest eigenvalues and associated eigenvectors of a real symmetric matrix, we consi...
The paper presents convergence estimates for a class of iterative methods for solving partial genera...
Includes bibliographical references (pages [42]-43)This paper studies the solution of symmetric posi...
A preconditioned simultaneous iteration method is described for the solution of the generalized eige...
Recently an efficient method (DACG) for the partial solution of the symmetric generalized eigenprobl...
We consider the problem of solving a symmetric, positive def-inite system of linear equations. The m...
In this paper, the convergence analysis of the conventional conjugate Gradient method was reviewed. ...
The computation of the smallest eigenvalues and eigenvectors of large numerical problems is a very i...
The computation of the smallest eigenvalues and eigenvectors of large numerical problems is a very i...
This article introduces and analyzes a new adaptive algorithm for solving symmetric positive definit...
We exploit an optimization method, called deflation-accelerated conjugate gradient (DACG), which seq...
AbstractThis paper deals with the convergence analysis of various preconditioned iterations to compu...
In this article a new family of preconditioners is introduced for symmetric positive definite linear...
AbstractIterative methods for solving large, sparse, symmetric eigenvalue problems often encounter c...
2In this paper, we present preconditioning techniques to accelerate the convergence of Krylov solve...
To compute the smallest eigenvalues and associated eigenvectors of a real symmetric matrix, we consi...
The paper presents convergence estimates for a class of iterative methods for solving partial genera...
Includes bibliographical references (pages [42]-43)This paper studies the solution of symmetric posi...
A preconditioned simultaneous iteration method is described for the solution of the generalized eige...
Recently an efficient method (DACG) for the partial solution of the symmetric generalized eigenprobl...
We consider the problem of solving a symmetric, positive def-inite system of linear equations. The m...