New delay-dependent exponential H(infinity) synchronization for uncertain neural networks with mixed time delays.

Hamid Reza Karimi, Huijun Gao
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引用次数: 393

Abstract

This paper establishes an exponential H(infinity) synchronization method for a class of uncertain master and slave neural networks (MSNNs) with mixed time delays, where the mixed delays comprise different neutral, discrete, and distributed time delays. The polytopic and the norm-bounded uncertainties are separately taken into consideration. An appropriate discretized Lyapunov-Krasovskii functional and some free-weighting matrices are utilized to establish some delay-dependent sufficient conditions for designing delayed state-feedback control as a synchronization law in terms of linear matrix inequalities under less restrictive conditions. The controller guarantees the exponential H(infinity) synchronization of the two coupled MSNNs regardless of their initial states. Detailed comparisons with existing results are made, and numerical simulations are carried out to demonstrate the effectiveness of the established synchronization laws.

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混合时滞不确定神经网络的新时滞相关指数H(∞)同步。
本文建立了一类具有混合时滞的不确定主从神经网络(msnn)的指数H(无穷)同步方法,其中混合时滞包括不同的中性、离散和分布时滞。分别考虑了多面体不确定性和范数有界不确定性。利用适当的离散Lyapunov-Krasovskii泛函和一些自由加权矩阵,建立了一些与延迟相关的充分条件,在较少约束条件下,将延迟状态反馈控制设计为线性矩阵不等式的同步律。该控制器保证了两个耦合msnn的指数H(无穷大)同步,无论其初始状态如何。与已有结果进行了详细比较,并进行了数值模拟,验证了所建立同步规律的有效性。
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