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Discrete-time stochastic impulsive BAM neural networks with leakage and mixed time delays: An exponential stability problem

机译:具有泄漏和混合时滞的离散时间随机脉冲BAM神经网络:一个指数稳定性问题

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摘要

In this paper, the stability analysis of impulsive discrete-time stochastic BAM neural networks with leakage and mixed time delays is investigated via some novel Lyapunov-Krasoviskii functional terms and effective techniques. For the target model, stochastic disturbances are described by Brownian motion. Then the result is further extended to address the problem of robust stability of uncertain discrete-time BAM neural networks. The conditions obtained here are expressed in terms of Linear Matrix Inequalities (LMIs), which can be easily checked by MATLAB LMI control toolbox. Finally, few numerical examples are presented to substantiate the effectiveness of the derived LMI-based stability conditions. (C) 2018 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
机译:本文通过一些新颖的Lyapunov-Krasoviskii函数项和有效技术研究了具有泄漏和混合时滞的脉冲离散时间随机BAM神经网络的稳定性。对于目标模型,随机干扰由布朗运动描述。然后将结果进一步扩展到解决不确定离散BAM神经网络的鲁棒稳定性问题。此处获得的条件以线性矩阵不等式(LMI)表示,可以通过MATLAB LMI控制工具箱轻松检查。最后,很少有数字示例可以证实基于LMI的稳定性条件的有效性。 (C)2018富兰克林研究所。由Elsevier Ltd.出版。保留所有权利。

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  • 来源
    《Journal of the Franklin Institute》 |2018年第10期|4404-4435|共32页
  • 作者单位

    Alagappa Univ, Dept Math, Karaikkudi 630004, Tamil Nadu, India;

    Alagappa Univ, Ramanujan Ctr Higher Math, Karaikkudi 630004, Tamil Nadu, India;

    Southeast Univ, Sch Math, Jiangsu Prov Key Lab Networked Collect Intelligen, Nanjing 211189, Jiangsu, Peoples R China;

    Shandong Normal Univ, Sch Math & Stat, Jinan 250014, Shandong, Peoples R China;

    Maejo Univ, Dept Math, Fac Sci, Chiang Mai, Thailand;

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  • 入库时间 2022-08-18 02:57:39

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