记忆电阻器
爆裂
混乱的
吸引子
振荡(细胞信号)
联轴节(管道)
生物神经元模型
拓扑(电路)
人工神经网络
生物系统
功率(物理)
数学
控制理论(社会学)
计算机科学
统计物理学
人工智能
物理
数学分析
材料科学
神经科学
控制(管理)
化学
量子力学
生物化学
组合数学
冶金
生物
作者
Lili Huang,Shaotian Wang,Tengfei Lei,K. X. Huang,Chunbiao Li
标识
DOI:10.1142/s0218127424500226
摘要
Local activity could be the source for complexity. In this study, a multistable locally active memristor is proposed, whose nonvolatile memory, as well as locally active characteristics, is validated by the power-off plot and DC [Formula: see text]–[Formula: see text] plot. Based on the two-dimensional Hindmarsh–Rose neuron and a one-dimensional Hopfield neuron, a simple neural network is constructed by connecting the two neurons with the locally active memristor. Coexisting multiple firing patterns under different initial conditions are investigated according to the controlled coupling factor. The results suggest that the system exhibits coexisting periodic and chaotic bursting with different firing patterns. Complex firing only occurs in the locally active area of the defined memristor, meanwhile the system shows a periodic oscillation in the passive area. Beyond this, the coupled neurons exhibit the specific phenomenon of attractor growing in the locally active region of the memristor. The circuit simulations by Power Simulation (PSIM) are included confirming the numerical simulations and theoretic analysis.
科研通智能强力驱动
Strongly Powered by AbleSci AI