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《Computer Engineering and Applications》 2006-32
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Model of Wavelet Hopfield Neural Network and its Applications in Optimization

XU Yao-qun1,2,SUN Ming2 (1.Center for Control Theory and Guidance Technology,Harbin Institute of Technology,Harbin 150001,China; 2.Institute of Computer and Information Engineering,Harbin University of Commerce,Harbin 150028,China)  
This paper presents a new model of Hopfield neural network which is called Wavelet Hopfield Neural Network(WHNN) by taking place of the sigmoid function with Morlet wavelet function.The WHNN summits a satisfied accurate effect because the Morlet function not only has the further ability in local approaching but has a nature of higher nonlinear.Finally,an example of function optimization is given to show that the Wavelet Hopfield Neural Network has a more accurate effect than the Hopfield Neural Network.
【Fund】： 黑龙江省青年科学基金资助(QC03C03);; 哈尔滨市青年科学基金资助(2005AFQXJ040);; 黑龙江省教育厅科学技术项目(10553019)。
【CateGory Index】： TP183
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