DocumentCode
3273119
Title
Evolving wavelet neural networks
Author
Yao, Susu ; Wei, Chengjian ; He, Zhenya
Author_Institution
Dept. of Radio Eng., Southeast Univ., Nanjing, China
Volume
4
fYear
1995
fDate
Nov/Dec 1995
Firstpage
1851
Abstract
A wavelet neural network with evolutionary programming is proposed in this paper. Unlike the conventional backpropagation training algorithm, the evolutionary programming does not require gradient information and can provide a stochastic optimal search. The proposed method is used to approximate nonlinear functions and solve classification problems. Some experimental results are proposed to show the potential of the evolving wavelet neural networks
Keywords
feedforward neural nets; function approximation; genetic algorithms; learning (artificial intelligence); pattern classification; search problems; wavelet transforms; classification problems; evolutionary programming; evolving wavelet neural networks; nonlinear functions; stochastic optimal search; Continuous wavelet transforms; Feedforward neural networks; Feeds; Function approximation; Genetic programming; Neural networks; Neurons; Signal analysis; Wavelet analysis; Wavelet transforms;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1995. Proceedings., IEEE International Conference on
Conference_Location
Perth, WA
Print_ISBN
0-7803-2768-3
Type
conf
DOI
10.1109/ICNN.1995.488903
Filename
488903
Link To Document