Improved synchronization analysis of competitive neural networks with time-varying delays
Adnène Arbi
 University of Kairouan; University of Carthage, Tunisia
Jinde Cao
Southeast University, China; King Abdulaziz University, Saudi Arabia
Ahmed Alsaedi
King Abdulaziz University, Saudi Arabia
Published 2018-02-20


competitive neural networks
time-varying delays
global exponential synchronization
Lyapunov functional

How to Cite

Arbi A., Cao J. and Alsaedi A. (2018) “Improved synchronization analysis of competitive neural networks with time-varying delays”, Nonlinear Analysis: Modelling and Control, 23(1), pp. 82-107. doi: 10.15388/NA.2018.1.7.


Synchronization and control are two very important aspects of any dynamical systems. Among various kinds of nonlinear systems, competitive neural network holds a very important place due to its application in diverse fields. The model is general enough to include, as subclass, the most famous neural network models such as competitive neural networks, cellular neural networks and Hopfield neural networks. In this paper, the problem of feedback controller design to guarantee synchronization for competitive neural networks with time-varying delays is investigated. The goal of this work is to derive an existent criterion of the controller for the exponential synchronization between drive and response neutral-type competitive neural networks with time-varying delays. The method used in this brief is based on feedback control gain matrix by using the Lyapunov stability theory. The synchronization conditions are given in terms of LMIs. To the best of our knowledge, the results presented here are novel and generalize some previous results. Some numerical simulations are also represented graphically to validate the effectiveness and advantages of our theoretical results.

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Please read the Copyright Notice in Journal Policy