An Evolutionary Wavelet Network and Its Training Method

摘要：

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.

关键词： evolutionary wavelet network principal component analysis oja algorithm hybrid genetic algorithm

作者: Liu Shou-sheng Ding Yong Liu Hai-feng

作者单位: nstitute of Science PLA University of Science and Technology Nanjing, China College of Automation Nanjing University of Aeronautics and Astronautics Nanjing, China Institute of Science PLA University of Science and Technology Nanjing, China

会议类型: 国际会议

会议名称: The 2010 International Conference on Computer Application and System Modeling(2010计算机应用与系统建模国际会议 ICCASM 2010)

会议地点: 太原

会议语种:英文

页码: 379-383

在线出版日期: 2010-10-22（万方平台首次上网日期，不代表论文的发表时间）