Finding Roots of Polynomials Based on Root Moments

摘要：

This paper proposes using root moment method to find the roots of arbitrary polynomials. It has been proved that feedforward neural networks (FNN) trained with constrained learning (CL) back propagation (BP) algorithm can be used to estimate the distributions of roots of polynomials. It has been found, however, that using the different priori information implicit in the polynomials for CL-BP algorithm will result in different training time and different estimate values. By comparison, we find that the root moment method implicit in the polynomials can obviously lower the training time and leads to more accurate estimates. Therefore, in this paper the root moment method is employed to find the roots of arbitrary polynomials. This paper presents some computer simulation results, which support our claims.

关键词： Feedforward Neural Networks Roots Polynomials Root Moments Constrained Learning.

作者: De-Shuang Huang

作者单位: The Key Lab of Agriculture Information Technology, Hefei Institute of Intelligent Machines,Chinese Academy of Sciences, P.O.Box 1130, Hefei, Anhui 230031, China

会议类型: 国际会议

会议名称: 8th International Conference on Neural Information Processing(ICONIP 2001)(第八届国际神经信息处理大会)

会议地点: 上海

会议语种:英文

页码: 1603-1609

在线出版日期: 2001-11-14（万方平台首次上网日期，不代表论文的发表时间）