DocumentCode
3481874
Title
A primal neural network for solving nonlinear equations and inequalities
Author
Yunong Zhang ; Shuzhi Sam Ge
Author_Institution
Dept. of Electron. & Electr. Eng., Strathclyde Univ., Glasgow
Volume
2
fYear
2004
fDate
1-3 Dec. 2004
Firstpage
1232
Lastpage
1237
Abstract
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
Keywords
mathematics computing; neural nets; nonlinear equations; dynamical constraint; dynamical inequalities; nonlinear equations; nonlinear inequalities; primal neural network; Computer networks; Hopfield neural networks; Kinematics; Manipulators; Neural network hardware; Neural networks; Nonlinear equations; Power engineering and energy; Recurrent neural networks; Robot sensing systems;
fLanguage
English
Publisher
ieee
Conference_Titel
Cybernetics and Intelligent Systems, 2004 IEEE Conference on
Conference_Location
Singapore
Print_ISBN
0-7803-8643-4
Type
conf
DOI
10.1109/ICCIS.2004.1460767
Filename
1460767
Link To Document