Robust Numerical Methods in Polynomial Algebra with Approximate Data

具有近似数据的多项式代数中的鲁棒数值方法

• 批准号: 0715127
• 负责人: Zhonggang Zeng
• 金额: $ 12.5万
• 依托单位: Northeastern Illinois University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-08-01 至 2012-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0715127&HistoricalAwards=false
• 关键词: Robust; Numerical; Methods; Polynomial; Algebra

This project aims at continuing development of reliable, accurate and efficient numerical algorithms for approximate polynomial algebra, along with implementations for expanding the capacity of a software toolbox ApaTools. In addition to those robust algorithms/software developed under previous NSF support, The PI proposes to design and implement algorithms for three fundamental algebraic problems: the approximate irreducible factorization of multivariate polynomials,identification of the multiplicity structure, and numerical elimination in solving polynomial systems. This research is to be carried out in the intersection of computer algebra and numerical analysis with an outcome consists of algorithms and software packages for solving mathematical problems. The results of this project are expected to supply critical tools for application areas such as robotics, molecular conformation, chemical equilibrium, automatic control, and other branches of mathematics such as algebraic geometry.

该项目旨在继续开发可靠、准确和有效的近似多项式代数数值算法，沿着扩展软件工具箱ApaTools的能力。 除了在以前NSF支持下开发的那些强大的算法/软件之外，PI还提出设计和实现三个基本代数问题的算法：多元多项式的近似不可约因式分解，多重性结构的识别以及求解多项式系统的数值消除。这项研究是在计算机代数和数值分析的交叉点进行的，其结果包括用于解决数学问题的算法和软件包。 该项目的成果有望为机器人、分子构象、化学平衡、自动控制等应用领域以及代数几何等其他数学分支提供关键工具。