Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/68197
Title: A partition-based recursive approach for finding higher-order polynomial roots using constrained learning neural networks
Other Titles: 基于神经网络的递推分块方法求任意高阶多项式的根
Authors: Huang, DS
Chi, Z 
Issue Date: 2003
Publisher: 中國科學雜誌社
Source: 中國科學. E輯 (Science in China. Series E), 2003, v. 33, no. 12, p. 1115-1124 How to cite?
Journal: 中國科學. E輯 (Science in China. Series E) 
Abstract: 提出一种新的基于约束学习神经网络的递推分块方法,来分批(块)求解任意高阶多项式的任意数(小于多项式的阶)个根(包括复根).同时给出了基于多项式中根与系数间的约束关系构造的用于求根的BP网络约束学习算法,提出了对应的学习参数的自适应选择方法.实验结果表明,这种分块神经求根方法,相对传统方法,能够快速有效地获得任意高阶多项式对应的根.
URI: http://hdl.handle.net/10397/68197
ISSN: 1006-9275
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