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Generalized augmented matrix preconditioning approach and its application to iterative solution of ill-conditioned algebraic systems

机译:广义增强矩阵预处理方法及其在病态代数系统迭代解中的应用

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摘要

The present work is devoted to a class of preconditioners based on the augmented matrix approach considered earlier by two of the present authors. It presents some generalizations of the subspace-correction schemes studied earlier and gives a brief comparison of the developed technique with a somewhat similar deflation algorithm. The developed preconditioners are able to improve significantly an eigenvalue distribution of certain severely ill-conditioned algebraic systems by using properly chosen projection matrices, which correct the low-frequency components in the spectrum. One of the main advantages of the proposed approach is the possibility of using inexact solvers within the projectors. Another attractive feature of the developed method is that it can be easily combined with other preconditioners, for instance, those which correct the high-frequency eigenmodes. [References: 21]
机译:本工作致力于基于其中两位作者较早考虑的增强矩阵方法的一类预处理器。它介绍了较早研究的子空间校正方案的一些概括,并简要介绍了所开发技术与某种类似的放气算法的比较。通过使用正确选择的投影矩阵来校正频谱中的低频分量,已开发的预处理器能够显着改善某些病情严重的代数系统的特征值分布。所提出的方法的主要优点之一是可以在投影仪中使用不精确的求解器。所开发方法的另一个吸引人的特点是它可以轻松地与其他预处理器结合使用,例如那些可以校正高频本征模式的预处理器。 [参考:21]

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