Title
Global synchronization of coupled delayed memristive reaction-diffusion neural networks.
Abstract
This paper focuses on the global exponential synchronization of multiple memristive reaction–diffusion neural networks (MRDNNs) with time delay. Due to introducing the influences of space as well as time on state variables and replacing resistors with memristors in circuit realization, the state-dependent partial differential mathematical model of MRDNN is more general and realistic than traditional neural network model. Based on Lyapunov functional theory, Divergence theorem and inequality techniques, global exponential synchronization criteria of coupled delayed MRDNNs are derived via directed and undirected nonlinear coupling. Finally, three numerical simulation examples are presented to verify the feasibility of our main results.
Year
DOI
Venue
2020
10.1016/j.neunet.2019.12.016
Neural Networks
Keywords
Field
DocType
Neural network,Memristor,Reaction–diffusion,Exponential synchronization,Coupling topology
Topology,Synchronization,Mathematical optimization,Memristor,Computer simulation,Divergence theorem,Partial derivative,State variable,Artificial neural network,Reaction–diffusion system,Mathematics
Journal
Volume
Issue
ISSN
123
C
0893-6080
Citations 
PageRank 
References 
1
0.35
0
Authors
4
Name
Order
Citations
PageRank
Shiqin Wang1153.18
Zhenyuan Guo2898.75
Shiping Wen3123172.34
Tingwen Huang45684310.24