时变时滞hopfield神经网络的鲁棒稳定性新准则

Fang Liu, Yong He, Yong Li, M. Dong
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引用次数: 0

摘要

研究了时变时滞Hopfield神经网络的鲁棒稳定性问题。通过构造合适的Lyapunov-Krasovskii泛函,得到了两个新的基于lmi的时滞相关鲁棒稳定性判据。该方法不仅保留了Lyapunov-Krasovskii泛函导数中有用的项,而且考虑了时滞、其上界及其差之间的关系,具有较低的保守性。最后通过数值算例验证了所提方法的优点和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Novel delay-dependent robust stability criteria of hopfield neural networks with time-varying delay
This paper investigates the robust stability problem of Hopfield neural networks(HNNs) with time-varying delay. Two novel LMI-based delay-dependent robust stability criteria are obtained by constructing appropriate Lyapunov-Krasovskii functional. This new criteria based on the free-weighting matrices approach prove to be less conservativeness, which not only retain any useful terms in the derivative of Lyapunov-Krasovskii functional, but also consider the relationship among the time-delay, its upper bound and their difference. Finally, some numerical examples are given to demonstrate its merits and effectiveness of the proposed methods.
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