脉冲时间窗延迟神经网络的指数稳定性分析

Zhenzhen Wu, Chuandong Li
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引用次数: 1

摘要

在几乎所有关于脉冲系统的先前出版物中,所涉及的脉冲都是固定瞬间。然而,在许多实际应用中,不能提前规定脉冲力矩。因此,本文建立了具有时滞和脉冲时间窗的广义神经网络模型。然后,利用李雅普诺夫稳定性理论方法,导出了几个新颖且易于证明的充分条件,证明了涉及脉冲时间窗的模型是全局指数稳定的。此外,还构造了指数收敛率与脉冲各参数相结合的框架。最后,通过数值模拟验证了理论结果的有效性。
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Exponential stability analysis of delayed neural networks with impulsive time window
In almost all of the previous publications about the impulsive systems, the impulses involved are fixed instants. However, in many actual applications, impulsive moments can not be prescribed ahead of schedule. Hence, in this manuscript, a generalized model of neural networks with delays and impulsive time window is formulated. And then, through the use of lyapunov stability theory method, several original and easy-to-prove sufficient conditions are derived to notarize that the model which concerning the impulsive time window is global exponential stable. Moreover a framework combining the exponential convergence rate with the various parameters of impulsive is constructed. Finally, the effectiveness of the theoretical results are demonstrated by the numerical simulations.
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