Finite-time synchronization of competitive neural networks with mixed delays

Xinsong Yang,Tingting Su

doi:10.3934/dcdsb.2016115

Abstract

In this paper, finite-time synchronization of competitive neural networks (CNNs) with bounded time-varying discrete and distributed delays (mixed delays) is investigated. A simple controller is added to response (slave) system such that it can be synchronized with the driving (master) CNN in a setting time. By introducing a suitable Lyapunov-Krasovskii's functional and utilizing some inequalities, several sufficient conditions are obtained to ensure the control object. Moreover, the setting time is explicitly given. Different from previous results, the setting is related to both the initial value of error system and the time delays. Finally, numerical examples are given to show the effectiveness of the theoretical results.

Highlights

In the past decades, much attention has been attracted to chaos control and synchronization due to their important applications in image processing and secure communication [15], [11]
Motivated by the above discussions, in this paper, we investigate finite-time synchronization of drive-response competitive neural networks (CNNs) with mixed delays by using a simple discontinuous controller
Finite-time synchronization of CNNS with mixed delays has been studied without using existing finitetime stability theorem

Summary

Introduction

Much attention has been attracted to chaos control and synchronization due to their important applications in image processing and secure communication [15], [11]. Exponential stochastic synchronization of coupled memristor-based neural networks was studied in [22], and synchronization induced by temporal delays in pulse-coupled neural networks was investigated in [9]. Another kind of neural networks, called competitive neural networks (CNNs), has received increasing attention of researchers [10], [23]. Authors in [20] further investigated the problem of exponential synchronization of switched stochastic CNNs with both interval time-varying delays and distributed delays.

Objectives

Conclusion