SAOR预条件共轭梯度法

Jianguo Wang, G. Meng
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引用次数: 0

摘要

对于求解大型的稀疏对称正线性方程组,经典CG方法的局限性已经众所周知。因此,我们采用了预条件共轭梯度(PCG)方法。该方法的关键是预调节器的构造。考虑到SAOR迭代矩阵法不是对称分裂的,将交替迭代法与SAOR迭代法结合,提出了一类预置共轭梯度法。对于该方法的条件数,我们将其称为SAOR-PCG,我们进行了理论分析,表明获得了较好的条件数。最后,给出了该算法的具体实现,并给出了数值结果来说明该算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SAOR Preconditioned Conjugate Gradient Method
For solving the large sparse symmetric and positive system of linear equations, the limitations of classical CG methods are now well known. So we exploit the preconditioned conjugate gradient (PCG) method. The key of this method is the construction of preconditioner. Consider SAOR iteration matrix method is not symmetric splitting, so we combine Alternating method with SAOR iteration method and present a class of preconditioned conjugate gradient method. The condition number for this method, which we refer to as SAOR-PCG, we develop a theoretical analysis that show that the better condition number is achieved. Furthermore, the Algorithm has been implemented and numerical results are included to illustrate the effectiveness of our approach.
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