Synchronization of memristive FitzHugh-Nagumo neural networks

被引：3
作者：
You, Yuncheng
Tian, Jing [2 ]
Tu, Junyi [1 ,3 ]
机构：
[1] Univ S Florida, Tampa, FL 33620 USA
[2] Towson Univ, Towson, MD 21252 USA
[3] Salisbury Univ, Salisbury, MD 21801 USA
来源：
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION | 2023年 / 125卷
关键词：
Memristive FitzHugh-Nagumo equations; Dissipative dynamics; Exponential synchronization; Coupling strength; Neural network;
D O I：
10.1016/j.cnsns.2023.107405
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
A new mathematical model of neural networks described by diffusive FitzHugh-Nagumo equations with memristors and linear synaptic coupling is proposed and investigated. The existence of absorbing set for the solution semiflow in the energy space is proved and global dynamics of the memristive neural networks are dissipative. Through uniform estimates and maneuver of integral inequalities on the interneuron difference equations, it is shown that exponential synchronization of the neural network at a uniform convergence rate occurs if the coupling strength satisfies a threshold condition explicitly expressed by the system parameters, which is illustrated and verified by numerical simulations. & COPY; 2023 Elsevier B.V. All rights reserved.
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页数：15
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