记忆电阻器
偏移量(计算机科学)
混乱的
同步(交流)
拓扑(电路)
计算机科学
控制理论(社会学)
平衡点
联轴节(管道)
同步
生物神经元模型
人工神经网络
物理
频道(广播)
非线性系统
电信
材料科学
工程类
电气工程
人工智能
控制(管理)
量子力学
冶金
程序设计语言
作者
Han Bao,Xihong Yu,Yunzhen Zhang,Xiaofeng Liu,Mo Chen
标识
DOI:10.1016/j.chaos.2023.114167
摘要
Memristors can be thought of as special connection synapses with internal states that regulate synchronous behavior or energy propagation between neurons in a neural network. By connecting two memristive Hindmarsh-Rose (mHR) neurons with one memristor coupling, this paper synthesizes a memristor-coupled mHR neuron (MC-mHRN) network without equilibrium point. For this network, the synchronization condition regulated by the initial condition-offset (ICO) of the memristive channel are derived theoretically, and the ICO-regulating synchronous dynamics is evaluated numerically. Furthermore, the Hamiltonian energy of mHR neuron is studied by Helmholtz's theorem, and the ICO-regulating energy diversity is analyzed numerically. It is demonstrated that the coupling strength and initial condition of the memristive channel can regulate the synchronous dynamics and energy diversity in the MC-mHRN network, thus achieving complete synchronization as well as energy balance. Consequently, the two mHR neurons in hidden chaotic firing modes deliver field energy via memristive channel until the fully synchronized energy balance is achieved. In addition, a digital platform of the MC-mHRN network is fabricated, and the experimental results validate the numerical ones of the synchronous dynamics.
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