Chaos synchronization of stochastic reaction-diffusion time-delay neural networks via non-fragile output-feedback control

This paper addresses the issue of non-fragile output-feedback control for master-slave chaos synchronization of reaction-diffusion time-delay neural networks subject to stochastic disturbances. Two types of norm-bounded multiplicative gain perturbations are taken into account. By the Lyapunov functi...

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Bibliographic Details
Published inApplied mathematics and computation Vol. 354; pp. 115 - 127
Main Authors Tai, Weipeng, Teng, Qingyong, Zhou, Youmei, Zhou, Jianping, Wang, Zhen
Format Journal Article
LanguageEnglish
Published Elsevier Inc 01.08.2019
Subjects
Chaos synchronization
Neural network
Output feedback
Reaction diffusion
Stochastic disturbance
Time delay
Reaction diffusion
Stochastic disturbance
Neural network
Time delay
Chaos synchronization
Output feedback
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ISSN0096-3003
1873-5649
DOI10.1016/j.amc.2019.02.028

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Summary:This paper addresses the issue of non-fragile output-feedback control for master-slave chaos synchronization of reaction-diffusion time-delay neural networks subject to stochastic disturbances. Two types of norm-bounded multiplicative gain perturbations are taken into account. By the Lyapunov functional method and stochastic stability theory, a delay-independent criterion for the mean-square asymptotic synchronization of the master network and the unforced salve network is derived. It is shown that the criterion is a necessary condition of a recent delay-dependent criterion. On the basis of the proposed analysis result and with the help of some decoupling techniques, constructive approaches for the design of non-fragile output-feedback controller are developed. Finally, two examples are employed to demonstrate the applicability and low conservatism of the present analysis and design approaches.
ISSN:0096-3003
1873-5649
DOI:10.1016/j.amc.2019.02.028