改进迭代改进

ACM '71 Pub Date : 1900-01-01 DOI:10.1145/800184.810539
E. Puccinelli
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引用次数: 0

摘要

本文描述了一种迭代改进矩阵a分解为两个矩阵B和C的乘积的方案。尽管B和C可能是完全一般的矩阵,但该方案在矩阵的LU和QR分解中最实际适用。提出的方案首先被证明可以改善给定矩阵a的扰动L和U因子,然后被证明当其他方法(如直接三角分解)惨败时,该过程将允许求解条件恶劣的线性方程组。最后,即使直接三角分解等方法有效,但必须对初始解进行迭代改进,所提出的方案在一定条件下也可以获得类似的结果,并且证明更经济。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improving iterative improvement
This paper describes a scheme for iteratively improving the decomposition of a given matrix A into the product of two matrices B and C. Although B and C may be completely general matrices, the scheme is most practically applicable in the LU and QR decompositions of a matrix. The proposed scheme is first shown to improve perturbed L and U factors of a given matrix A. Next, it is shown that this process will allow for the solution of a badly conditioned system of linear equations when other methods, such as direct triangular decomposition, fail miserably. Finally even when a method such as direct triangular decomposition works, but iterative improvement of the initial solution must be made, the proposed scheme may achieve comparable results and prove to be more economical under certain conditions.
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