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

机译:随机反应扩散时间延迟神经网络的混沌同步通过非易碎输出反馈控制

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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.
机译:本文解决了对随机紊乱的反应扩散时间延迟神经网络的主从混沌同步的非脆弱输出反馈控制问题。 考虑两种类型的规范乘法增益扰动。 通过Lyapunov功能方法和随机稳定性理论,导出了主网络和未加工的烧焦网络的平均方形渐近同步的延迟无关标准。 结果表明,标准是近期延迟相关标准的必要条件。 在所提出的分析结果的基础上,借助于一些去耦技术,开发了非易碎输出反馈控制器设计的建设性方法。 最后,采用两个示例来证明目前分析和设计方法的适用性和低保守性。 (c)2019 Elsevier Inc.保留所有权利。

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