记忆电阻器
神经形态工程学
联轴节(管道)
物理
混乱的
分叉
非线性系统
生物神经元模型
神经元
振荡(细胞信号)
对称性破坏
复杂动力学
混乱的边缘
拓扑(电路)
统计物理学
人工神经网络
计算机科学
神经科学
数学
量子力学
数学分析
人工智能
组合数学
工程类
生物
机械工程
遗传学
作者
Yujiao Dong,Rongrong Guo,Yan Liang,Jiu‐jun Yang,Guangyi Wang
出处
期刊:Chaos
[American Institute of Physics]
日期:2024-08-01
卷期号:34 (8)
被引量:1
摘要
Brain-like dynamics require third-order or higher-order complexity. In order to investigate the coupling neuromorphic behaviors of identical third-order memristive neurons, this paper begins with the aim of exploring two identical neuron based dynamics under distinct operating regimes and coupling strengths. Without coupling, the single neuron can exhibit resting states, periodic spikes, or chaos depending on the bias condition. The uncoupled resting neurons can be activated by resistive coupling, inducing inhomogeneous resting states (static Smale paradox) and inhomogeneous spikes (dynamic Smale paradox) due to the edge of chaos regime. Considering the single neuron at the periodic spikes or chaotic states, the coupled neurons can mimic shocking oscillation death, non-periodic asynchronization, and periodic synchronization via the Hopf bifurcation theory. From the above analyses, an artificial ring neural network is constructed using 100 memristive neurons and resistive synapses to further study the coupled mechanism, generating exotic spatiotemporal patterns such as chimera death, amplitude chimera, solitary states, and asynchronization because of symmetry breaking. This sheds new light on exploring exotic spatiotemporal patterns of networks based on memristive neurons from the perspective of the nonlinear circuit theory.
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