4.7 Article

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

期刊

APPLIED MATHEMATICS AND COMPUTATION
卷 354, 期 -, 页码 115-127

出版社

ELSEVIER SCIENCE INC
DOI: 10.1016/j.amc.2019.02.028

关键词

Neural network; Time delay; Reaction diffusion; Stochastic disturbance; Output feedback; Chaos synchronization

资金

  1. National Natural Science Foundation of China [61503002, 61573008]
  2. Key Research and Development Project of Anhui Province [1704a0902033]
  3. Natural Science Foundation of the Anhui Higher Education Institutions [KJ2017A064, KJ2018ZD007]

向作者/读者索取更多资源

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. (C) 2019 Elsevier Inc. All rights reserved.

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