DocumentCode
1031793
Title
Wavelet networks
Author
Zhang, Qinghua ; Benveniste, Albert
Author_Institution
Linkopings Tekniska Hogskola, Sweden
Volume
3
Issue
6
fYear
1992
fDate
11/1/1992 12:00:00 AM
Firstpage
889
Lastpage
898
Abstract
A wavelet network concept, which is based on wavelet transform theory, is proposed as an alternative to feedforward neural networks for approximating arbitrary nonlinear functions. The basic idea is to replace the neurons by `wavelons´, i.e., computing units obtained by cascading an affine transform and a multidimensional wavelet. Then these affine transforms and the synaptic weights must be identified from possibly noise corrupted input/output data. An algorithm of backpropagation type is proposed for wavelet network training, and experimental results are reported
Keywords
backpropagation; feedforward neural nets; wavelet transforms; affine transform; arbitrary nonlinear functions approximation; backpropagation; feedforward neural networks; learning algorithm; multidimensional wavelet; synaptic weights; wavelet network; wavelet transform theory; Backpropagation algorithms; Continuous wavelet transforms; Convergence; Discrete transforms; Feedforward neural networks; Helium; Neural networks; Nonlinear systems; Power system modeling; Wavelet transforms;
fLanguage
English
Journal_Title
Neural Networks, IEEE Transactions on
Publisher
ieee
ISSN
1045-9227
Type
jour
DOI
10.1109/72.165591
Filename
165591
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