DocumentCode :
312492
Title :
Study on the function of fuzzy data curve in fuzzy-neural network system
Author :
Jiang, Zhifeng ; Liu, Zemin
Author_Institution :
Dept. of Radio Eng., Beijing Univ. of Posts & Telecommun., China
Volume :
1
fYear :
1996
fDate :
26-29 Nov 1996
Firstpage :
11
Abstract :
This paper presents an improved fuzzy-neural network (FNN) model, which is a simple but effective fuzzy-rule based model about complex systems. Its architecture could be determined only by using the input-output data of the system. In the FNN model, the membership functions and weights would be adjusted optimally through the high speed BP learning principle, and the number of neurons in the inference layer would be confirmed through fuzzy data curves. Viewing the neural network as a fuzzy model gives an insight into the real system, and provides a method to simplify the neural network
Keywords :
backpropagation; fuzzy neural nets; knowledge based systems; large-scale systems; multilayer perceptrons; neural net architecture; complex systems; fuzzy data curve; fuzzy-neural network model; fuzzy-neural network system; fuzzy-rule based model; high speed BP learning principle; inference layer; input-output data; membership functions; multilayered neural network; neural network architecture; neurons; weights; Convergence; Fuzzy logic; Fuzzy neural networks; Fuzzy reasoning; Fuzzy systems; Intelligent networks; Multi-layer neural network; Neural networks; Neurons; Telecommunications;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
TENCON '96. Proceedings., 1996 IEEE TENCON. Digital Signal Processing Applications
Conference_Location :
Perth, WA
Print_ISBN :
0-7803-3679-8
Type :
conf
DOI :
10.1109/TENCON.1996.608687
Filename :
608687
Link To Document :
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