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首页> 外文期刊>Numerical algorithms >A new quasi-minimal residual method based on a biconjugate A-orthonormalization procedure and coupled two-term recurrences
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A new quasi-minimal residual method based on a biconjugate A-orthonormalization procedure and coupled two-term recurrences

机译:基于双共轭A正交归一化程序和耦合二项递归的新的拟最小残差方法

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摘要

Recently, some novel variants of Lanczos-type methods were explored that are based on the biconjugate A-orthonormalization process. Numerical experiments coming from some physical problems indicate that these new methods are competitive with or superior to other popular Krylov subspace methods. Among them, the biconjugate A-orthogonal residual (BiCOR) method is the archetype method. However, like the biconjugate gradient (BiCG) method, the BiCOR method often shows irregular convergence behavior which can lead to numerical instability. To overcome this drawback, motivated by the effectiveness and robustness of the quasi-minimal residual (QMR) method, we derive a new QMR-like approach based on the coupled two-term biconjugate A-orthonormalization process and simple recurrences instead of the QR decomposition. Some convergence properties are given, and the special case for solving complex symmetric linear system is considered. Finally, numerical experiments are reported to illustrate the performances of our methods and their preconditioners on linear systems discretizing the Helmholtz equation or taken from Florida Sparse Matrix Collection.
机译:最近,基于双共轭A正交归一化过程,探索了Lanczos型方法的一些新颖变体。来自某些物理问题的数值实验表明,这些新方法可以与其他流行的Krylov子空间方法竞争或优于其他方法。其中,双共轭A正交残差(BiCOR)方法是原型方法。但是,像双共轭梯度(BiCG)方法一样,BiCOR方法经常显示出不规则的收敛行为,这可能导致数值不稳定。为了克服此缺点,受准最小残留(QMR)方法的有效性和鲁棒性的启发,我们基于耦合的二项双共轭A-正交归一化过程和简单的递归代替QR分解,推导了一种类似于QMR的新方法。给出了一些收敛性,并考虑了求解复杂对称线性系统的特殊情况。最后,报道了数值实验,以说明我们的方法及其预处理器在离散Helmholtz方程或取自Florida Sparse Matrix Collection的线性系统上的性能。

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