Semi-Conjugate Direction Methods for Real Positive Definite Systems
被引:0
作者:
J. Y. Yuan
论文数: 0引用数: 0
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机构:Universidade Federal do Paraná,Departamento de Matemática
J. Y. Yuan
G. H. Golub
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h-index: 0
机构:Universidade Federal do Paraná,Departamento de Matemática
G. H. Golub
R. J. Plemmons
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h-index: 0
机构:Universidade Federal do Paraná,Departamento de Matemática
R. J. Plemmons
W. A. G. Cecílio
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h-index: 0
机构:Universidade Federal do Paraná,Departamento de Matemática
W. A. G. Cecílio
机构:
[1] Universidade Federal do Paraná,Departamento de Matemática
[2] Stanford University,Department of Computer Science
[3] Wake Forest University,Department of Computer Science
[4] Pontifícia Universidade Católica do Paraná,Departamento de Matemática
来源:
BIT Numerical Mathematics
|
2004年
/
44卷
关键词:
left conjugate direction vectors;
right conjugate direction vectors;
left conjugate direction method;
semi-conjugate direction method;
LU decomposition;
conjugate gradient method;
Gaussian elimination;
solution of nonsymmetric linear systems;
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摘要:
In this preliminary work, left and right conjugate direction vectors are defined for nonsymmetric, nonsingular matrices A and some properties of these vectors are studied. A left conjugate direction (LCD) method for solving nonsymmetric systems of linear equations is proposed. The method has no breakdown for real positive definite systems. The method reduces to the usual conjugate gradient method when A is symmetric positive definite. A finite termination property of the semi-conjugate direction method is shown, providing a new simple proof of the finite termination property of conjugate gradient methods. The new method is well defined for all nonsingular M-matrices. Some techniques for overcoming breakdown are suggested for general nonsymmetric A. The connection between the semi-conjugate direction method and LU decomposition is established. The semi-conjugate direction method is successfully applied to solve some sample linear systems arising from linear partial differential equations, with attractive convergence rates. Some numerical experiments show the benefits of this method in comparison to well-known methods.