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
Link To Document :
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