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Exponential Lagrange Stability for Markovian Jump Uncertain Neural Networks with Leakage Delay and Mixed Time-Varying Delays via Impulsive Control

机译:具有脉冲时滞和时变混合时滞的马尔可夫跳跃不确定神经网络的指数拉格朗日稳定性

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摘要

The problem of exponential Lagrange stability analysis of Markovian jump neural networks with leakage delay and mixed time-varying delays is studied in this paper. By utilizing the Lyapunov functional method, employing free-weighting matrix approach and inequality techniques in matrix form, we establish several novel stability criteria such that, for all admissible parameter uncertainties, the suggested neural network is exponentially stable in Lagrange sense. The derived criteria are expressed in terms of linear matrix inequalities (LMIs). A numerical example is provided to manifest the validity of the proposed results.
机译:研究了具有泄漏时滞和时变混合时滞的马尔可夫跳跃神经网络的指数Lagrange稳定性分析问题。通过使用Lyapunov泛函方法,采用自由加权矩阵方法和矩阵形式的不等式技术,我们建立了几个新颖的稳定性标准,从而对于所有可容许的参数不确定性,建议的神经网络在Lagrange意义上是指数稳定的。得出的标准以线性矩阵不等式(LMI)表示。数值例子说明了所提出结果的有效性。

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  • 来源
    《Mathematical Problems in Engineering》 |2018年第7期|6489517.1-6489517.15|共15页
  • 作者单位

    Thiruvalluvar Univ, Dept Math, Vellore 632115, Tamil Nadu, India;

    Thiruvalluvar Univ, Dept Math, Vellore 632115, Tamil Nadu, India;

    Nanjing Normal Univ, Sch Math Sci, Nanjing 210023, Jiangsu, Peoples R China;

    Nanjing Normal Univ, Sch Math Sci, Nanjing 210023, Jiangsu, Peoples R China;

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