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《Journal of Changchun Post and Telecommunication Institute》 2005-05
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Improved Wavelet Neural Network Model and Its Application

YU Fan-hua ~(1,2a),LIU Ren-yun~(2b),ZHAO Hong-wei~(1), ZANG Xue-bai~(1),YE Xin~(1)(1Center of Computer Teaching and Research,Jilin University,Changchun 130026,China;2a-^College of Information Technology;2b-^College of Mathematics, Changchun Teachers College, Changchun 130032,China)  
A conjugationg gradient algorithm based on Local learning strategy is presented to improve approximation quality and extensive capability of the WNN(Wavelet Neural Network), as well as to Improve the parameters optimization and process simulation in the machining of vibration drilling on variation parameters. And then the three input weight-|values are selected for the improved net model by taking advantage of the grey relevancy analysis. The selection principle for dilation and translation factors of wavelet function and network weight-|value is also given. The experiment shows that the proposal method improves the simulation effect and network performance.
【Fund】: 国家自然科学基金资助项目(59675059);; 吉林省科技厅资助项目(20010570)
【CateGory Index】: TP183
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