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陈永红, 徐健学, 方同. 规范形网络中的混沌吸引子[J]. 力学学报, 1998, 30(6): 676-681. DOI: 10.6052/0459-1879-1998-6-1995-177
引用本文: 陈永红, 徐健学, 方同. 规范形网络中的混沌吸引子[J]. 力学学报, 1998, 30(6): 676-681. DOI: 10.6052/0459-1879-1998-6-1995-177
A CHAOTIC ATTRACTOR IN THE NORMAL FORM NETWORK[J]. Chinese Journal of Theoretical and Applied Mechanics, 1998, 30(6): 676-681. DOI: 10.6052/0459-1879-1998-6-1995-177
Citation: A CHAOTIC ATTRACTOR IN THE NORMAL FORM NETWORK[J]. Chinese Journal of Theoretical and Applied Mechanics, 1998, 30(6): 676-681. DOI: 10.6052/0459-1879-1998-6-1995-177

规范形网络中的混沌吸引子

A CHAOTIC ATTRACTOR IN THE NORMAL FORM NETWORK

  • 摘要: 讨论多余维Hopf分叉三阶规范形的普适开折形成的网络更进一步的复杂动力学行为.通过对余维二Hopf分叉的规范形网络多级分叉的分析,发现在参数空间的某个区域会出现二环面,将S形非线性加入规范形网络,在出现二环面的区域内可以出现混沌.本文给出了该混沌吸引子的相图及其二阶Poincare映射的图景.由这些图可以看到该混沌吸引子具有非常奇妙的形态:某些二阶Poincare映射像一只逼真的蝴蝶.

     

    Abstract: Biological experiments of mammalian brain have shown that real neural systems exhibit a range of phenomena such as oscillations, phase-locking and even chaos. The chaotic behaviors simulate the information processing mechanisms of the real neural systems at a higher level. In this paper the bifurcation and chaos of the high order correlation networks will be studied.In some previous discussions about the high order correlation neural networks, we learned that the high order correlation networks expected to ...

     

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