Paper Info
Title
Exponential synchronization of multiple impulsive discrete-time memristor-based neural networks with stochastic perturbations and time-varying delays
Abstract
This paper investigates the impulsive synchronization problems of a class of multiple discrete-time memristor-based neural networks (DTMNNs) with stochastic perturbations and time-varying delays. The impulsive synchronization problems include the synchronization preservation for stable DTMNNs under impulsive perturbations and the achievement of synchronization for unstable DTMNNs under impulsive control. Firstly, we construct a class of multiple DTMNNs with stochastic perturbations and time-varying delays. Secondly, two sets of sufficient synchronization conditions are respectively established by constructing appropriate Lyapunov functionals and using two different methods. Under impulsive perturbations, the synchronization preservation for stable DTMNNs is achieved as long as the first set of synchronization conditions is satisfied. Moreover, the desired impulsive control matrix is derived by solving the second set of synchronization conditions. Finally, in order to verify the effectiveness of the theoretical results, we present two numerical examples.
Year
DOI
Venue
2020
10.1016/j.neucom.2020.01.110
Neurocomputing
Keywords
DocType
Volume
Memristor-based neural networks,Exponential synchronization,Stochastic perturbations,Impulsive perturbations,Impulsive control
Journal
392
ISSN
Citations 
PageRank 
0925-2312
2
0.35
References 
Authors
0
4
Name
Order
Citations
PageRank
Huiyuan Li1413.53
Jianán Fang221516.62
xiaofan li37912.44
Tingwen Huang45684310.24