Paper Info
Title
Hybrid adaptive synchronization strategy for linearly coupled reaction-diffusion neural networks with time-varying coupling strength.
Abstract
In this article, the adaptive synchronization control for an array of coupled reaction diffusion neural networks with time-varying coupling strength and delays is considered. A novel hybrid adaptive learning law consists of discrete updating law for the unknown time-varying coupling coefficient and continuous adaptive law for the unknown time-invariant parameter is derived, which extends the adaptive synchronization control for the constant coupling coefficient to the time-varying one. Through constructing a novel Lyapunov-Krasovskii functional, the synchronization controller and criterion are presented. Furthermore, to take the disturbance into consideration, the H-infinity synchronization criterion is presented, also. Finally, a numerical example is given and some comparisons are performed to demonstrate the effectiveness of the synchronization strategies. (c) 2017 Elsevier B.V. All rights reserved.
Year
DOI
Venue
2018
10.1016/j.neucom.2017.10.022
NEUROCOMPUTING
Keywords
Field
DocType
Synchronization,Reaction-diffusion neural networks,Time-varying coupling,H-infinity synchronization
Synchronization,Control theory,Computer science,Control theory,Coupling strength,Artificial neural network,Adaptive learning,Coupling coefficient of resonators
Journal
Volume
ISSN
Citations 
275
0925-2312
5
PageRank 
References 
Authors
0.42
28
2
Name
Order
Citations
PageRank
Chao He171.12
Jun-Min LI239036.09