A preconditioning technique to improve the convergence of the Gauss-Seidel method applied to symmetric linear systems while preserving symmetry is proposed. The preconditioner is of the form I + K and can be applied an arbitrary number of times. It is shown that under certain conditions the application of the preconditioner a finite number of steps reduces the matrix to a diagonal. A series of numerical experiments using matrices from spatial discretizations of partial differential equations demonstrates that both versions of the preconditioner, point and block version, exhibit lower iteration counts than its non-symmetric version. To cite this article: J. Cajigas, I. Arenas, P. Castillo, An acceleration technique for the Gauss-Seidel met...
AbstractWhen convergent Jacobi or Gauss-Seidel iterations can be applied to solve systems of linear ...
AbstractIn 2002, H. Kotakemori et al. proposed the modified Gauss–Seidel (MGS) method for solving th...
For symmetric systems, rigorous convergence bounds can be obtained which depend only on the eigenval...
Se propone una técnica de precondicionamiento para mejorar la convergencia del método Gauss-Seidel a...
A preconditioning technique based on the application of a fixedbut arbitrary number of I + Smax step...
AbstractIt has recently been reported that the convergence of the preconditioned Gauss-Seidel method...
Abstract. For Ax = b, it has recently been reported that the conver-gence of the preconditioned Gaus...
In this paper, the modified Gauss-Seidel method with the new preconditioner for solving the linear s...
AbstractIn 1991 A. D. Gunawardena et al. reported that the convergence rate of the Gauss-Seidel meth...
Although large and sparse linear systems can be solved using iterative methods, its number of iterat...
The aim of this survey is to review some recent developments in devising efficient preconditioners f...
AbstractIn recent years, a number of preconditioners have been applied to linear systems [A.D. Gunaw...
The symmetric Sinc-Galerkin method applied to a separable second-order self-adjoint elliptic boundar...
AbstractA method to construct preconditioners to a symmetric, positive definite matrix based on part...
Analysis of real life problems often results in linear systems of equations for which solutions are ...
AbstractWhen convergent Jacobi or Gauss-Seidel iterations can be applied to solve systems of linear ...
AbstractIn 2002, H. Kotakemori et al. proposed the modified Gauss–Seidel (MGS) method for solving th...
For symmetric systems, rigorous convergence bounds can be obtained which depend only on the eigenval...
Se propone una técnica de precondicionamiento para mejorar la convergencia del método Gauss-Seidel a...
A preconditioning technique based on the application of a fixedbut arbitrary number of I + Smax step...
AbstractIt has recently been reported that the convergence of the preconditioned Gauss-Seidel method...
Abstract. For Ax = b, it has recently been reported that the conver-gence of the preconditioned Gaus...
In this paper, the modified Gauss-Seidel method with the new preconditioner for solving the linear s...
AbstractIn 1991 A. D. Gunawardena et al. reported that the convergence rate of the Gauss-Seidel meth...
Although large and sparse linear systems can be solved using iterative methods, its number of iterat...
The aim of this survey is to review some recent developments in devising efficient preconditioners f...
AbstractIn recent years, a number of preconditioners have been applied to linear systems [A.D. Gunaw...
The symmetric Sinc-Galerkin method applied to a separable second-order self-adjoint elliptic boundar...
AbstractA method to construct preconditioners to a symmetric, positive definite matrix based on part...
Analysis of real life problems often results in linear systems of equations for which solutions are ...
AbstractWhen convergent Jacobi or Gauss-Seidel iterations can be applied to solve systems of linear ...
AbstractIn 2002, H. Kotakemori et al. proposed the modified Gauss–Seidel (MGS) method for solving th...
For symmetric systems, rigorous convergence bounds can be obtained which depend only on the eigenval...