DocumentCode
820893
Title
Neural network controller using autotuning method for nonlinear functions
Author
Yamada, Takayuki ; Yabuta, Tetsuro
Author_Institution
NTT Telecommun. Field Syst., R&D Center, Ibaraki, Japan
Volume
3
Issue
4
fYear
1992
fDate
7/1/1992 12:00:00 AM
Firstpage
595
Lastpage
601
Abstract
An autotuning method for the optimum sigmoid function of neural networks is proposed. It is based on the steepest descent method. Simulated results using a learning-type direct controller confirm both the practicality and the characteristics of the autotuning method
Keywords
learning systems; neural nets; self-adjusting systems; autotuning; learning systems; learning-type direct controller; neural network controllers; nonlinear functions; optimum sigmoid function; Control systems; Convergence; Cost function; Design methodology; Difference equations; Neural networks; Nonlinear control systems; Nonlinear dynamical systems; Robots; Shape;
fLanguage
English
Journal_Title
Neural Networks, IEEE Transactions on
Publisher
ieee
ISSN
1045-9227
Type
jour
DOI
10.1109/72.143373
Filename
143373
Link To Document