广义Halanay不等式及其在无界时变时滞神经网络中的应用。

IEEE transactions on neural networks Pub Date : 2011-09-01 Epub Date: 2011-07-18 DOI:10.1109/TNN.2011.2160987
Bo Liu, Wenlian Lu, Tianping Chen
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引用次数: 77

摘要

在本文中,我们讨论了广义Halanay不等式的一些变体,它们在讨论延迟神经网络、积分-微分系统和Volterra泛函微分方程的耗散性和稳定性方面是有用的。我们提供了Halanay不等式的一些推广,它比现有的结果更准确。作为应用,我们讨论了具有无限延迟的Hopfield神经网络的不变量集、耗散同步和全局渐近稳定性。我们还证明了具有无界时变时滞的动力系统是全局渐近稳定的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Generalized Halanay inequalities and their applications to neural networks with unbounded time-varying delays.

In this brief, we discuss some variants of generalized Halanay inequalities that are useful in the discussion of dissipativity and stability of delayed neural networks, integro-differential systems, and Volterra functional differential equations. We provide some generalizations of the Halanay inequality, which is more accurate than the existing results. As applications, we discuss invariant set, dissipative synchronization, and global asymptotic stability for the Hopfield neural networks with infinite delays. We also prove that the dynamical systems with unbounded time-varying delays are globally asymptotically stable.

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来源期刊
IEEE transactions on neural networks
IEEE transactions on neural networks 工程技术-工程:电子与电气
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2
审稿时长
8.7 months
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