Memristors-coupled neuron models with multiple firing patterns and homogeneous and heterogeneous multistability  

作　　者：Xuan Wang Santo Banerjee Yinghong Cao Jun Mou 王暄;Santo Banerjee;曹颖鸿;牟俊(School of Information Science and Engineering,Dalian Polytechnic University,Dalian 116034,China;Department of Mathematical Sciences,Giuseppe Luigi Lagrange,Politecnico di Torino,Corso Duca degli Abruzzi 24,Torino,Italy)

机构地区：[1]School of Information Science and Engineering,Dalian Polytechnic University,Dalian 116034,China [2]Department of Mathematical Sciences,Giuseppe Luigi Lagrange,Politecnico di Torino,Corso Duca degli Abruzzi 24,Torino,Italy

出　　处：《Chinese Physics B》2024年第10期176-189,共14页中国物理B（英文版）

基　　金：supported by the National Natural Science Foundation of China(Grant No.62061014);Technological Innovation Projects in the Field of Artificial Intelligence in Liaoning province(Grant No.2023JH26/10300011);Basic Scientific Research Projects in Department of Education of Liaoning Province(Grant No.JYTZD2023021).

摘　　要：Memristors are extensively used to estimate the external electromagnetic stimulation and synapses for neurons.In this paper,two distinct scenarios,i.e.,an ideal memristor serves as external electromagnetic stimulation and a locally active memristor serves as a synapse,are formulated to investigate the impact of a memristor on a two-dimensional Hindmarsh-Rose neuron model.Numerical simulations show that the neuronal models in different scenarios have multiple burst firing patterns.The introduction of the memristor makes the neuronal model exhibit complex dynamical behaviors.Finally,the simulation circuit and DSP hardware implementation results validate the physical mechanism,as well as the reliability of the biological neuron model.

关 键 词：MEMRISTOR MULTISTABILITY Hamilton energy firing pattern Neuron model hardware implementation 

分 类 号：Q189[生物学—神经生物学] TN60[生物学—普通生物学]