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Convergence Results on Iteration Algorithms to Linear Systems

机译:线性系统迭代算法的收敛结果

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摘要

In order to solve the large scale linear systems, backward and Jacobi iteration algorithms are employed. The convergence is the most important issue. In this paper, a unified backward iterative matrix is proposed. It shows that some well-known iterative algorithms can be deduced with it. The most important result is that the convergence results have been proved. Firstly, the spectral radius of the Jacobi iterative matrix is positive and the one of backward iterative matrix is strongly positive (lager than a positive constant). Secondly, the mentioned two iterations have the same convergence results (convergence or divergence simultaneously). Finally, some numerical experiments show that the proposed algorithms are correct and have the merit of backward methods.
机译:为了解决大规模线性系统,采用了反向和雅可比迭代算法。收敛是最重要的问题。本文提出了一个统一的后向迭代矩阵。它表明可以推导出一些众所周知的迭代算法。最重要的结果是证明了收敛结果。首先,雅可比迭代矩阵的谱半径为正,而后向迭代矩阵的谱半径为强正(比正常数滞后)。其次,上述两个迭代具有相同的收敛结果(同时收敛或发散)。最后,一些数值实验表明所提出的算法是正确的,并且具有后向方法的优点。

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