稀疏结构与高斯消去

I. S. Duff, A. Erisman, C. Gear, John Reid
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引用次数: 35

摘要

本文整理并讨论了关于矩阵稀疏性结构的一些结果。如果一个矩阵是不可约的,高斯消去法产生一个LU分解,其中L在除最后一列以外的每一列对角线下方至少有一个元素,U在除最后一行以外的每一列对角线右侧至少有一个元素。如果用这个分解来解方程Ax=b,中间向量在它的最后一个分量中有一个分量,并且解x是满的。而且,A的逆矩阵是满的。当矩阵可约时,这些结果适用于其块三角形的对角线块。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sparsity structure and Gaussian elimination
In this paper we collate and discuss some results on the sparsity structure of a matrix. If a matrix is irreducible, Gaussian elimination yields an LU factorization in which L has at least one entry beneath the diagonal in every column except the last and U has at least one entry to the right of the diagonal in every row except the last. If this factorization is used to solve the equation Ax=b, the intermediate vector has an entry in its last component and the solution x is full. Furthermore, the inverse of A is full.Where the matrix is reducible, these results are applicable to the diagonal blocks of its block triangular form.
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