一种计算小因子多项式最大公项的概率算法

Yang Zhang, Xin Qian, Qidi You, Xuan Zhou, Xiyong Zhang, Yang Wang
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引用次数: 0

摘要

在早期的工作中,Knuth提出了一种算法来减少多项式的欧几里得算法中的系数增长,称为子结式算法。然而,输出多项式可能有一个小的因子,可以被删除。后来,贝尔电话实验室的布朗以另一种方式展示了子结果,他添加了一个叫做“”的变体,并给出了一种计算变体的方法。然而,这种方法并没有正确地确定每一个地名。在本文中,我们将给出一个概率算法来确定变异𝜏正确在大多数情况下,通过添加几个步骤,而不是计算𝑡(𝑥)当给定𝑓(𝑥)和𝑔(𝑥)∈ℤ[𝑥],在𝑡(𝑥)满足𝑠(𝑥)𝑓(𝑥)+𝑡(𝑥)𝑔(𝑥)=𝑟(𝑥),这里𝑡(𝑥)𝑠(𝑥)∈ℤ[𝑥]
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Probabilistic Algorithm for Computation of Polynomial Greatest Common with Smaller Factors
In the earlier work, Knuth present an algorithm to decrease the coefficient growth in the Euclidean algorithm of polynomials called subresultant algorithm. However, the output polynomials may have a small factor which can be removed. Then later, Brown of Bell Telephone Laboratories showed the subresultant in another way by adding a variant called 𝜏 and gave a way to compute the variant. Nevertheless, the way failed to determine every𝜏 correctly. In this paper, we will give a probabilistic algorithm to determine the variant 𝜏 correctly in most cases by adding a few steps instead of computing 𝑡(𝑥) when given 𝑓(𝑥) and𝑔(𝑥) ∈ ℤ[𝑥], where 𝑡(𝑥) satisfies that 𝑠(𝑥)𝑓(𝑥) + 𝑡(𝑥)𝑔(𝑥) = 𝑟(𝑥), here 𝑡(𝑥), 𝑠(𝑥) ∈ ℤ[𝑥]
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