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SAOR Preconditioned Conjugate Gradient Method

机译:Saor预处理共轭梯度法

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摘要

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.
机译:为了求解线性方程的大稀疏对称和正系统,现在是众所周知的CG方法的局限性。因此,我们利用预处理的共轭梯度(PCG)方法。这种方法的关键是建设预处理器。考虑Saor迭代矩阵方法不是对称分裂,所以我们将交替方法与Saor迭代方法组合并呈现一类预先说明的共轭梯度方法。我们称为Saor-PCG的这种方法的条件号,我们开发了一个理论分析,表明实现了更好的条件号。此外,已经实现了算法,包括数值结果来说明我们方法的有效性。

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