Title :
An Evolutionary Wavelet Network and its training method
Author :
Shou-Sheng, Liu ; Yong, Ding ; Hai-Feng, Liu
Author_Institution :
Inst. of Sci., PLA Univ. of Sci. & Technol., Nanjing, China
Abstract :
Aimed at the problems of the curse of dimensionality and the lack of robustness for wavelet neural network, an optimization method based on principal component analysis for wavelet network structure is presented. However, this method is easily plunge into local minimum points when principal components are solved by Oja iterative algorithm. Genetic Algorithm which has good characteristic in global optimization can remedy the deficiency of Oja algorithm. In this paper, wavelet network is optimized by Hybrid Genetic Algorithm which is composed of genetic algorithm and Oja algorithm. This Evolutionary Wavelet Network(EWN)has effectively solved the problems of wavelet network, such as overmany nods and the lack of robustness. The simulation results show the efficiency of EWN.
Keywords :
feedforward neural nets; genetic algorithms; iterative methods; principal component analysis; wavelet transforms; Oja iterative algorithm; evolutionary wavelet neural network; hybrid genetic algorithm; optimization method; principal component analysis; wavelet network structure; Algorithm design and analysis; Artificial neural networks; Discrete wavelet transforms; Eigenvalues and eigenfunctions; Principal component analysis; Wavelet analysis; Evolutionary Wavelet Network; Hybrid Genetic Algorithm; Oja algorithm; principal component analysis;
Conference_Titel :
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-7235-2
Electronic_ISBN :
978-1-4244-7237-6
DOI :
10.1109/ICCASM.2010.5623012