A single neuron model with memristive synaptic weight

被引：33

作者：

Hua, Mengjie ^{[1
]}

Bao, Han ^{[1
]}

Wu, Huagan ^{[1
]}

Xu, Quan ^{[1
]}

Bao, Bocheng ^{[1
]}

机构：

[1] Changzhou Univ, Sch Microelect & Control Engn, Changzhou 213164, Peoples R China

来源：

CHINESE JOURNAL OF PHYSICS | 2022年 / 76卷

关键词：

Neuron model; memristive synaptic weight; neuron dynamics; coexisting bifurcation; hardware circuit; MULTIPLE ATTRACTORS; NUMERICAL-ANALYSES; NETWORK; DYNAMICS; CIRCUIT; DRIVEN; BRAIN; TIME;

D O I：

10.1016/j.cjph.2021.10.042

中图分类号：

O4 [物理学];

学科分类号：

0702 ;

摘要：

Synaptic connection weight in neuron is adaptive and memristive synaptic weight can be taken as a changeable connection weight. To exhibit its kinetic effect, a single neuron model with memristive synaptic weight is thereby presented. The memristive single neuron model has time-varying equilibrium points with the changes in number and stability, resulting in the appearance of complex neuron dynamics. Using multiple numerical analyses, complex neuron dynamics is studied in details, including parameter-related dynamics distributions, phase portraits with equilibrium stabilities, and coexisting bifurcation plots. Furthermore, with the analog circuit design, printed-circuit board (PCB)-based experiments are carried out. The physically captured results well validate the numerical ones.

引用

页码：217 / 227

页数：11

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