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首页> 外文期刊>Chaos >Synchronization of Rulkov neuron networks coupled by excitatory and inhibitory chemical synapses
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Synchronization of Rulkov neuron networks coupled by excitatory and inhibitory chemical synapses

机译:兴奋性和抑制化学突触的Rulkov Neuron网络的同步

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摘要

This paper takes into account a neuron network model in which the excitatory and the inhibitory Rulkov neurons interact each other through excitatory and inhibitory chemical coupling, respectively. Firstly, for two or more identical or non-identical Rulkov neurons, the existence conditions of the synchronization manifold of the fixed points are investigated, which have received less attention over the past decades. Secondly, the master stability equation of the arbitrarily connected neuron network under the existence conditions of the synchronization manifold is discussed. Thirdly, taking three identical Rulkov neurons as an example, some new results are presented: (1) topological structures that can make the synchronization manifold exist are given, (2) the stability of synchronization when different parameters change is discussed, and (3) the roles of the control parameters, the ratio, as well as the size of the coupling strength and sigmoid function are analyzed. Finally, for the chemical coupling between two non-identical neurons, the transversal system is given and the effect of two coupling strengths on synchronization is analyzed.
机译:本文考虑了神经元网络模型,其中兴奋性和抑制性Rulkov神经元分别通过兴奋性和抑制性化学偶联彼此相互作用。首先,对于两个或更多个相同或非相同的Rulkov神经元,研究了固定点的同步歧管的存在条件,这在过去几十年中受到更少的关注。其次,讨论了在同步歧管的存在条件下任意连接的神经元网络的主稳定性方程。第三,用三个相同的Rulkov神经元作为示例,提出了一些新结果:(1)给出了可以使同步歧管存在的拓扑结构,(2)讨论不同参数变化时同步的稳定性,(3)分析了控制参数,比率以及耦合强度和SIGMOID函数的尺寸的作用。最后,对于两个非相同神经元之间的化学偶联,对横向系统进行了分析,并分析了两个耦合强度对同步的影响。

著录项

  • 来源
    《Chaos》 |2019年第3期|共18页
  • 作者

    Ge Penghe; Cao Hongjun;

  • 作者单位

    Beijing Jiaotong Univ Dept Math Sch Sci Beijing 100044 Peoples R China;

    Beijing Jiaotong Univ Dept Math Sch Sci Beijing 100044 Peoples R China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 自然科学总论;
  • 关键词

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