Anti-synchronization of delayed memristive neural networks with leakage term and reaction–diffusion terms

作者:

Highlights:

摘要

In this paper, the global exponential anti-synchronization problem is studied for an array of delayed memristive neural networks (DMNNs) with leakage term and reaction–diffusion terms. Firstly, to investigate the exponential anti-synchronization problems, we will design two different types of controllers for the proposed systems. Secondly, via adopting Lyapunov functional method, the drive–response theory and some inequality techniques, several sufficient conditions are obtained to ensure the global exponential anti-synchronization of the proposed DMNNs with leakage term and reaction–diffusion terms. Specifically, the delays could be time-varying or constants in the leakage term. Compared with the previously research results, the proposed neural network models herein are more general, and the obtained results consider the diffusion effects, leakage delay and time-varying delays, and those results can improve and enrich the previously obtained results. At last, two numerical examples are provided to demonstrate the validity of the derived theoretical results.

论文关键词:Memristive neural networks,Exponential anti-synchronization,Leakage term,Time-varying delays,Reaction–diffusion terms

论文评审过程:Received 11 June 2021, Revised 10 September 2021, Accepted 22 September 2021, Available online 29 September 2021, Version of Record 7 October 2021.

论文官网地址:https://doi.org/10.1016/j.knosys.2021.107539