Synchronization and Adaptive Control of an Array of Linearly Coupled Reaction-Diffusion Neural Networks With Hybrid Coupling

In this paper, we propose a general array model of coupled reaction-diffusion neural networks with hybrid coupling, which is composed of spatial diffusion coupling and state coupling. By utilizing the Lyapunov functional method combined with the inequality techniques, a sufficient condition is given...

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Bibliographic Details
Published in:IEEE transactions on cybernetics 2014-08, Vol.44 (8), p.1350-1361
Main Authors: Wang, Jin-Liang, Wu, Huai-Ning
Format: Article
Language:English
Subjects:
Adaptive control
Adaptive coupling
Algorithms
Arrays
complex dynamical networks
Complex networks
Computer simulation
Couplings
Criteria
hybrid coupling
H∞ synchronization
Joining
Models, Neurological
Networks
Neural networks
Neural Networks (Computer)
Symmetric matrices
Synchronism
Synchronization
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Summary:In this paper, we propose a general array model of coupled reaction-diffusion neural networks with hybrid coupling, which is composed of spatial diffusion coupling and state coupling. By utilizing the Lyapunov functional method combined with the inequality techniques, a sufficient condition is given to ensure that the proposed network model is synchronized. In addition, when the external disturbances appear in the network, a criterion is obtained to guarantee the H ∞ synchronization of the network. Moreover, some adaptive strategies to tune the coupling strengths among network nodes are designed for reaching synchronization and H ∞ synchronization. Some criteria for synchronization and H ∞ synchronization are derived by using the designed adaptive laws. Numerical simulations are presented finally to demonstrate the effectiveness of the obtained theoretical results.
ISSN:2168-2267
2168-2275
DOI:10.1109/TCYB.2013.2283308