Hopf Bifurcation Analysis on a Tabu Learning Single Neuron Model in the Frequency Domain

摘要：

In this paper, a tabu learning single neuron model is investigated. By applying the frequency domain approach and analyzing the associated characteristic equation, the existence of bifurcation parameter for this model is determined. Furthermore, we found that if the memory decay rate is used as a bifurcation parameter, Hopf bifurcation occurs in the neuron. This means that a family of periodic solutions bifurcates out from the equilibrium when the bifurcation parameter exceeds a critical value. The direction and stability of the bifurcating periodic solutions are determine by the Nyquist criterion and the graphical Hopf bifurcation theorem. Some numerical simulations for justifying the theoretical analysis are also given.

作者: Xiaobing Zhou Yue Wu Yi Li Yalan Ye

作者单位: School of Computer Science and Engineering, University of Electronic Science and Technology of China,Chengdu 610054, China

会议类型: 国际会议

会议名称: 2006 International Conference on Communications,Circuits and Systems(第四届国际通信、电路与系统学术会议)

会议地点: 广西桂林

会议语种:英文

页码: 2042-2045

在线出版日期: 2006-06-25（万方平台首次上网日期，不代表论文的发表时间）