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Global exponential stability of Markovian jumping stochastic impulsive uncertain BAM neural networks with leakage mixed time delays and α-inverse Hölder activation functions

机译:具有泄漏混合时滞和α-逆Hölder激活函数的Markovian跳跃随机脉冲不确定BAM神经网络的全局指数稳定性

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摘要

This paper concerns the problem of enhanced results on robust finite time passivity for uncertain discrete time Markovian jumping BAM delayed neural networks with leakage delay. By implementing a proper Lyapunov–Krasovskii functional candidate, reciprocally convex combination method, and linear matrix inequality technique, we derive several sufficient conditions for varying the passivity of discrete time BAM neural networks. Further, some sufficient conditions for finite time boundedness and passivity for uncertainties are proposed by employing zero inequalities. Finally, the enhancement of the feasible region of the proposed criteria is shown via numerical examples with simulation to illustrate the applicability and usefulness of the proposed method.
机译:本文讨论了不确定的离散时间马尔可夫跳跃BAM时滞神经网络的鲁棒有限时间无源性提高结果的问题。通过实现适当的Lyapunov–Krasovskii函数候选,倒凸组合方法和线性矩阵不等式技术,我们得出了改变离散时间BAM神经网络无源性的几个充分条件。此外,通过采用零不等式,提出了一些有限时间有界性和不确定性被动性的充分条件。最后,通过数值算例和仿真表明了所提出准则的可行范围的增强,以说明所提出方法的适用性和实用性。

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