Impulsive Stabilization and Impulsive Synchronization of Discrete-Time Delayed Neural Networks

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 di...

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Bibliographic Details
Published in:IEEE transaction on neural networks and learning systems 2015-04, Vol.26 (4), p.734-748
Main Authors: Chen, Wu-Hua, Lu, Xiaomei, Zheng, Wei Xing
Format: Article
Language:English
Subjects:
Algorithms
Biological neural networks
Communication
Computer Simulation
Criteria
Delay
Delays
discrete-time neural networks
Dynamical systems
Humans
impulsive stabilization
impulsive synchronization
Mathematical model
Neural networks
Neural Networks (Computer)
Nonlinear Dynamics
Reaction Time
Stability
Stability criteria
Stabilization
Synchronism
Synchronization
Time Factors
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Summary: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.
ISSN:2162-237X
2162-2388
DOI:10.1109/TNNLS.2014.2322499