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Stochastic global exponential stability for neutral-type impulsive neural networks with mixed time-delays and Markovian jumping parameters

机译:具有混合时滞和马尔可夫跳跃参数的中立型脉冲神经网络的随机全局指数稳定性

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摘要

This paper investigates the problem of the global exponential stability for neutral-type impulsive neural networks with mixed delays and Markovian jumping parameters. The mixed delays include discrete and distributed time-delays and the jumping parameters are generated from a continuous time discrete state homogenous Markov process. Based on the Lyapunov functional, a sufficient criterion is derived in terms of linear matrix equality (LMI).
机译:本文研究了具有混合时滞和马尔可夫跳跃参数的中立型脉冲神经网络的全局指数稳定性问题。混合延迟包括离散和分布式时延,并且跳跃参数是从连续时间离散状态同质马尔可夫过程生成的。基于Lyapunov泛函,根据线性矩阵等式(LMI)得出了足够的标准。

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