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On Iterative Processes in the Krylov-Sonneveld Subspaces

机译:关于Krylov-Sonneveld子空间的迭代过程

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The iterative Induced Dimension Reduction (IDR) methods are considered for solving large systems of linear algebraic equations (SLAEs) with nonsingular nonsymmetric matrices. These approaches are investigated by many authors and are charach-terized sometimes as the alternative to the classical processes of Krylov type. The key moments of the IDR algorithms consist in the construction of the embedded Sonneveld subspaces' which have the decreasing dimensions and use the orthogonalization to some fixed subspace. Other independent approaches for research and optimization of the iterations are based on the augmented and modified Krylov subspaces by using the aggregation and deflation procedures with present various low rank approximations of the original matrices. The goal of this paper is to show, that IDR method in Sonneveld subspaces present an original interpretation of the modified algorithms in the Krylov subspaces. In particular, such description is given for the multi-preconditioned semi-conjugate direction methods which are actual for the parallel algebraic domain decomposition approaches.
机译:考虑迭代诱导的尺寸减少(IDR)方法,用于用非对称矩阵求解线性代数方程(SLAES)的大型系统。许多作者调查了这些方法,并且有时作为恰当是Krylov类型的经典过程的替代方案。 IDR算法的关键时刻在构建嵌入式Sonneveld子空间的构建中,该子空间具有减少的尺寸并使用正交化到某些固定子空间。研究和优化迭代的其他独立方法是基于增强和修改的Krylov子空间,通过使用具有原始矩阵的各种低秩近似的聚合和通货紧缩程序。本文的目标是展示,Sonneveld子空间中的IDR方法呈现了Krylov子空间中修改的算法的原始解释。特别地,给出了这样的描述,用于多次预处理的半共轭方向方法,其实际用于并行代数域分解方法。

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