DocumentCode
397834
Title
Multiwavelet neural network: a novel model
Author
Li, Xiaolan ; Gao, Xieping
Author_Institution
Nat. Lab. on Machine Perception, Peking Univ., Beijing, China
Volume
3
fYear
2003
fDate
5-8 Oct. 2003
Firstpage
2629
Abstract
A neural network is an efficient tool to solve nonlinear problem, but it is hard to determine its structure and it often settles in a local minimum. After combining the wavelet with it, the two key problems are solved. However, a new problem, so called "dimension disaster", appears, and solving it within the framework of a wavelet neural network (WNN) is not easy. We introduce a new neural network named multiwavelet neural network (MWNN), which not only preserves all the advantages of WNN, but also avoids the "dimension disaster". Several theorems are given and the experimental results validate the correctness of our theory.
Keywords
feedforward neural nets; wavelet transforms; dimension disaster; local minimum; multiwavelet neural network; nonlinear problem; Educational institutions; Feedforward neural networks; Frequency; Multi-layer neural network; Multiresolution analysis; Neural networks; Numerical analysis; Signal processing; Signal processing algorithms; Wavelet analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Man and Cybernetics, 2003. IEEE International Conference on
ISSN
1062-922X
Print_ISBN
0-7803-7952-7
Type
conf
DOI
10.1109/ICSMC.2003.1244280
Filename
1244280
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