时变离散和分布时滞神经网络的新的全局渐近稳定性

2008 3rd International Conference on Innovative Computing Information and Control Pub Date : 2008-06-18 DOI:10.1109/ICICIC.2008.385

Yonggang Chen, Yunrui Guo, Liang Wu

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引用次数: 0

摘要

研究了一类具有时变离散时滞和分布时滞的神经网络的全局渐近稳定性问题。基于Lyapunov泛函方法，利用估计Lyapunov泛函导数上界的新技术，导出了基于线性矩阵不等式的新的渐近稳定性判据。算例表明，该方法具有较好的保守性。

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New Global Asymptotic Stability for Neural Networks with Time-Varying Discrete and Distributed Delays

In this paper, the global asymptotic stability problem is considered for a class of neural networks with time-varying discrete and distributed delays. Based on the Lyapunov functional method, and by using the new technique for estimating the upper bound of the derivative of Lyapunov functional, the novel asymptotic stability criterion is derived in terms of linear matrix inequalities (LMIs). Two numerical examples are presented to show the less conservativeness of the proposed method.

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2008 3rd International Conference on Innovative Computing Information and Control

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