Global synchronization of coupled delayed memristive reaction-diffusion neural networks. Academic Article

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.

authors

• Huang, Tingwen

published proceedings

• Neural Netw

author list (cited authors)

• Wang, S., Guo, Z., Wen, S., & Huang, T.

citation count

• 30

complete list of authors

• Wang, Shiqin||Guo, Zhenyuan||Wen, Shiping||Huang, Tingwen

publication date

• March 2020

publisher

• Elsevier  Publisher

published in

• Neural Networks  Journal

keywords

• Coupling Topology
• Exponential Synchronization
• Memristor
• Models, Theoretical
• Neural Network
• Neural Networks, Computer
• Reaction–diffusion
• Time

PubMed Central ID

• 31901877

Digital Object Identifier (DOI)

• 10.1016/j.neunet.2019.12.016

start page

• 362

end page

• 371

volume

• 123

URL

• http://dx.doi.org/10.1016/j.neunet.2019.12.016