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首页> 外文期刊>International journal of systems science >Decentralised event-triggered impulsive synchronisation for semi-Markovian jump delayed neural networks with leakage delay and randomly occurring uncertainties
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Decentralised event-triggered impulsive synchronisation for semi-Markovian jump delayed neural networks with leakage delay and randomly occurring uncertainties

机译:具有泄漏延迟和随机不确定性的半马尔可夫跳跃延迟神经网络的分散事件触发脉冲同步

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摘要

This study examines the problem of decentralised event-triggered impulsive synchronisation for the semi-Markovian jump neutral type neural networks with leakage delay and randomly occurring uncertainties. An improved globally asymptotic stability criterion is derived to guarantee impulsive synchronisation of the response systems with the drive systems. In order to reduce the network traffic and the resource of computation, we propose a new decentralised event-triggered scheme for the considered delayed NNs. In order to make full use of the sawtooth structure characteristic of the sampling input delay, a discontinuous Lyapunov functional is proposed. By establishing a suitable Lyapunov-Krasovskii functional (LKF) with triple integral terms and applying Writinger based integral method, auxiliary function based integral inequalities, reciprocal convex approach and improved inequality techniques, a delay dependent stability criterion is derived in terms of linear matrix inequalities (LMIs). Finally, numerical examples are given to illustrate the effectiveness of the proposed results.
机译:本研究研究了具有泄漏延迟和随机不确定性的半马尔可夫跳跃中立型神经网络的分散事件触发脉冲同步问题。推导了改进的全局渐近稳定性准则,以确保响应系统与驱动系统的脉冲同步。为了减少网络流量和计算资源,我们针对所考虑的延迟神经网络提出了一种新的分散事件触发方案。为了充分利用采样输入延迟的锯齿结构特性,提出了一种不连续的Lyapunov函数。通过使用三重积分项建立合适的Lyapunov-Krasovskii泛函(LKF)并应用基于Writeer的积分方法,基于辅助函数的积分不等式,倒数凸方法和改进的不等式技术,根据线性矩阵不等式推导了依赖于延迟的稳定性准则( LMI)。最后,通过数值算例说明了所提出结果的有效性。

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