多稳态
爆裂
记忆电阻器
吸引子
混乱的
生物神经元模型
物理
计算机科学
非线性系统
生物系统
拓扑(电路)
人工神经网络
人工智能
神经科学
数学
工程类
电气工程
数学分析
生物
量子力学
作者
Sen Zhang,Chunbiao Li,Jiahao Zheng,Xiaoping Wang,Zhigang Zeng,Guanrong Chen
标识
DOI:10.1109/tie.2022.3225847
摘要
Thanks to their distinct synaptic plasticity and memory effects, memristors not only can mimic biological neuronal synapses but also can describe the influence of external electromagnetic radiation. This article proposes a novel memristive autapse-coupled neuron model (MACNM) using a locally active memristor as an autapse and simultaneously introducing a flux-controlled piecewise-nonlinear memristor to describe the external electromagnetic radiation. Theoretical analysis and numerical simulation results show that the MACNM is able to generate multiple numbers of grid multiscroll hidden attractors. Moreover, it can exhibit rich and complex hidden firing dynamics, including periodic spiking/bursting firing, chaotic spiking/bursting firing, as well as firing patterns transition. In particular, hidden firing multistability of five coexisting homogeneous chaotic bursting firing patterns with different offsets along the boosting route is discovered, giving raise to the interesting phenomenon of hidden homogeneous multistability. Finally, a circuit is designed to verify the physical feasibility of the abundant electrical activities in the proposed MACNM.
科研通智能强力驱动
Strongly Powered by AbleSci AI