不变流形
同步(交流)
中央歧管
歧管(流体力学)
非线性系统
特征向量
混乱的
控制理论(社会学)
同步网络
拓扑(电路)
混沌同步
指数稳定性
联轴节(管道)
数学
计算机科学
物理
数学分析
分叉
霍普夫分叉
材料科学
组合数学
工程类
机械工程
控制(管理)
量子力学
人工智能
冶金
作者
Penghe Ge,Libo Cheng,Hongjun Cao
出处
期刊:Chaos
[American Institute of Physics]
日期:2024-04-01
卷期号:34 (4)
被引量:4
摘要
This paper analyzes the complete synchronization of a three-layer Rulkov neuron network model connected by electrical synapses in the same layers and chemical synapses between adjacent layers. The outer coupling matrix of the network is not Laplacian as in linear coupling networks. We develop the master stability function method, in which the invariant manifold of the master stability equations (MSEs) does not correspond to the zero eigenvalues of the connection matrix. After giving the existence conditions of the synchronization manifold about the nonlinear chemical coupling, we investigate the dynamics of the synchronization manifold, which will be identical to that of a synchronous network by fixing the same parameters and initial values. The waveforms show that the transient chaotic windows and the transient approximate periodic windows with increased or decreased periods occur alternatively before asymptotic behaviors. Furthermore, the Lyapunov exponents of the MSEs indicate that the network with a periodic synchronization manifold can achieve complete synchronization, while the network with a chaotic synchronization manifold can not. Finally, we simulate the effects of small perturbations on the asymptotic regimes and the evolution routes for the synchronous periodic and the non-synchronous chaotic network.
科研通智能强力驱动
Strongly Powered by AbleSci AI