摘要
基于神经元的自反馈项可产生混沌的现象,将Gauss小波函数作为混沌神经元的自反馈项。分析了Gauss小波的尺度和平移参数对神经元动力学的影响,提出了自反馈连接权和Gauss小波尺度双重模拟退火的混沌神经元。构建了混沌神经网络模型,分析了由Gauss小波函数产生的附加能量函数对网络优化能力的影响。优化问题的仿真结果表明,该网络能够以较快的速度找到优化问题的全局最优解。
Based on the phenomena that the neuron＇s self-feedback can generate chaos,Gauss wavelet function is used as the self-feedback of chaotic neuron in this paper.The effect of the scale and shift parameters in Gauss wavelet on the neuron dynamics is analyzed and the chaotic neuron with double simulated annealing mechanisms realized respectively by the self-feedback connection weight and the Gauss wavelet scale is proposed.The chaotic neural network is constructed and the effect of the additional energy function generated by Gauss wavelet function on the optimization ability of the network is studied.The simulation results on optimization problems show that the proposed network can find the global optimum of the optimization problems with a faster speed.
出处
《计算机工程与应用》
CSCD
北大核心
2010年第11期42-45,共4页
Computer Engineering and Applications
基金
国家自然科学基金No.60474046
国家教育部新世纪人才支持计划No.NCET-04-0339~~
