DocumentCode :
3500530
Title :
Optimization of fixed Wavelet Neural Networks
Author :
Cordova, J.J. ; Yu, Wen
Author_Institution :
Dept. de Control Automatico, CINVESTAV-IPN, Mexico City, Mexico
fYear :
2011
fDate :
July 31 2011-Aug. 5 2011
Firstpage :
3003
Lastpage :
3007
Abstract :
In the construction of a Wavelet Neural Network, the number of neurons is determined by the traslation coefficient and by the dilations coefficient. Exists two ways to set the value of the traslation coefficients and dilation, one is considering the coefficients like a hidden layer of the network and the other way is establishing fixed values to those coefficients, where there remains the problem of establishing the number of fixed values to be taken, in this paper we present an algorithm to determine the number of fixed values, that they minimize a rate that depends on the approximation error and the number of neurons that are used.
Keywords :
approximation theory; function approximation; neural nets; optimisation; wavelet transforms; approximation error; dilation coefficient; fixed wavelet neural network optimization; network hidden layer; traslation coefficient; Approximation algorithms; Approximation methods; Arrays; Biological neural networks; Neurons; Wavelet transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks (IJCNN), The 2011 International Joint Conference on
Conference_Location :
San Jose, CA
ISSN :
2161-4393
Print_ISBN :
978-1-4244-9635-8
Type :
conf
DOI :
10.1109/IJCNN.2011.6033616
Filename :
6033616
Link To Document :
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