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

Weipeng Tai, Qingyong Teng, Youmei Zhou, Jianping Zhou and Zhen Wang

Applied Mathematics and Computation, 2019, vol. 354, issue C, 115-127

Abstract: 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.

Keywords: Neural network; Time delay; Reaction diffusion; Stochastic disturbance; Output feedback; Chaos synchronization (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (7)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:354:y:2019:i:c:p:115-127

DOI: 10.1016/j.amc.2019.02.028

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