Polynomial root-finding with matrix eigen-solving

V. Pan
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引用次数: 1

Abstract

Numerical matrix methods are increasingly popular for polynomial root-finding. This approach usually amounts to the application of the QR algorithm to the highly structured Frobenius companion matrix of the input polynomial. The structure, however, is routinely destroyed already in the first iteration steps. To accelerate this approach, we exploit the matrix structure of the Frobenius and generalized companion matrices, employ various known and novel techniques for eigen-solving and polynomial root-finding, and in addition to the Frobenius input allow other highly structured generalized companion matrices. Employing polynomial root-finders for eigen-solving is a harder task because of the potential numerical stability problems, but we found some new promising directions, particularly for sparse and/or structured input matrices.
用矩阵特征求解多项式求根
数值矩阵法在多项式求根中越来越受欢迎。这种方法通常相当于将QR算法应用于输入多项式的高度结构化Frobenius伴矩阵。然而,在第一个迭代步骤中,该结构通常已经被破坏。为了加速这一方法,我们利用了Frobenius和广义伴矩阵的矩阵结构,采用了各种已知的和新颖的特征求解和多项式寻根技术,并且除了Frobenius输入之外,还允许其他高度结构化的广义伴矩阵。由于潜在的数值稳定性问题,使用多项式寻根器进行特征求解是一项更困难的任务,但我们发现了一些新的有希望的方向,特别是对于稀疏和/或结构化输入矩阵。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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