Paper Info
Title
Impulsive stabilization and impulsive synchronization of discrete-time delayed neural networks.
Abstract
This paper investigates the problems of impulsive stabilization and impulsive synchronization of discrete-time delayed neural networks (DDNNs). Two types of DDNNs with stabilizing impulses are studied. By introducing the time-varying Lyapunov functional to capture the dynamical characteristics of discrete-time impulsive delayed neural networks (DIDNNs) and by using a convex combination technique, new exponential stability criteria are derived in terms of linear matrix inequalities. The stability criteria for DIDNNs are independent of the size of time delay but rely on the lengths of impulsive intervals. With the newly obtained stability results, sufficient conditions on the existence of linear-state feedback impulsive controllers are derived. Moreover, a novel impulsive synchronization scheme for two identical DDNNs is proposed. The novel impulsive synchronization scheme allows synchronizing two identical DDNNs with unknown delays. Simulation results are given to validate the effectiveness of the proposed criteria of impulsive stabilization and impulsive synchronization of DDNNs. Finally, an application of the obtained impulsive synchronization result for two identical chaotic DDNNs to a secure communication scheme is presented.
Year
DOI
Venue
2015
10.1109/TNNLS.2014.2322499
IEEE Trans. Neural Netw. Learning Syst.
Keywords
Field
DocType
discrete-time neural networks,delay,impulsive synchronization,time-varying lyapunov functional,linear-state feedback impulsive controller,neurocontrollers,asymptotic stability,impulsive stabilization,time-varying systems,discrete-time impulsive delayed neural network,state feedback,convex combination technique,delays,didnn,exponential stability,impulsive synchronization.,discrete time systems,linear matrix inequalities,linear systems,geometry,synchronisation,lyapunov methods,synchronization,mathematical model
Synchronization,Control theory,Convex combination,Computer science,Matrix (mathematics),Synchronizing,Exponential stability,Discrete time and continuous time,Chaotic,Artificial neural network
Journal
Volume
Issue
ISSN
26
4
2162-2388
Citations 
PageRank 
References 
38
1.06
28
Authors
3
Name
Order
Citations
PageRank
Wu-Hua Chen186958.24
Xiaomei Lu21248.38
Wei Xing Zheng34266274.73