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arXiv 2011.10924cs.SCmath.AG
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一元多项式向量的$μ$ -基的一种新算法

A new algorithm for computing $μ$-bases of the univariate polynomial vector

Dingkang Wang, Hesong Wang, Fanghui Xiao

摘要:

本文刻划了Groebner基与u-基之间的关系:n元多项式的合合模关于项-位置单项式阶的任何极小Groebner基都是它的u-基。此外,基于gcd计算,我们用递归的方法构造了syzygy模的一个自由基。根据这种关系和所构造的自由基,给出了计算合合模u-基的一种新算法。在合理的假设下,算法的理论复杂度为O(n^3d^2),其中d是输入n个多项式的最大次数。我们已经在Maple中实现了该算法(MinGb)。实验数据以及与Song和Goldman(2009)开发的现有算法(SG算法)和Hong等人(2017)开发的现有算法(HHK算法)的性能比较表明,当n和d足够大时,MinGb算法比SG算法更高效,而MinGb算法和HHK算法都有各自的优势。

英文摘要:

In this paper, we characterized the relationship between Groebner bases and u-bases: any minimal Groebner basis of the syzygy module for n univariate polynomials with respect to the term-over-position monomial order is its u-basis. Moreover, based on the gcd computation, we construct a free basis of the syzygy module by the recursive way. According to this relationship and the constructed free basis, a new algorithm for computing u-bases of the syzygy module is presented. The theoretical complexity of the algorithm is O(n^3d^2) under a reasonable assumption, where d is the maximum degree of the input n polynomials. We have implemented this algorithm (MinGb) in Maple. Experimental data and performance comparison with the existing algorithms developed by Song and Goldman (2009) (SG algorithm) and Hong et al. (2017) (HHK algorithm) show that MinGb algorithm is more efficient than SG algorithm when n and d are sufficiently large, while MinGb algorithm and HHK algorithm both have their own advantages.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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