A primal neural network for solving nonlinear equations and inequalities

被引：0
|
作者：
Zhang, YN [1 ]
Ge, SZS [1 ]
机构：
[1] Univ Strathclyde, Dept Elect & Elect Engn, Glasgow G1 1XW, Lanark, Scotland
来源：
2004 IEEE CONFERENCE ON CYBERNETICS AND INTELLIGENT SYSTEMS, VOLS 1 AND 2 | 2004年
关键词：
primal neural network; equations and inequalities; nonuniqueness; minimum effort inverse kinematics;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, the concept and utility of primal neural networks are introduced for the context of dynamical constraints or inequalities. Based on the neural-network design experience on solving linear equations/inequalities, we generalize a primal neural network to handling the nonlinear situation. Numerical examples (including the robotic applications) are given to demonstrate the effectiveness of the primal network.
引用
收藏
页码：1232 / 1237
页数：6
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