基于lmi的时变时滞神经网络全局鲁棒稳定性新准则

2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI) Pub Date : 2012-10-01 DOI:10.1109/ICACI.2012.6463197

Zhenhua Huang, B. Li

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引用次数: 0

摘要

本文给出了具有时变时滞的神经网络全局鲁棒渐近稳定的几个充分条件。在此基础上，导出了若干线性矩阵不等式准则。将目前的标准与以前的标准进行比较。最后通过算例验证了所得结果的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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New LMI-based criteria for global robust stability of neural networks with time-varying delays

In this paper, some sufficient conditions for global robust asymptotical stability of neural networks with time-varying delays are presented. On basis of the obtained results, some linear matrix inequality (LMI) criteria are derived. A comparison of the present criteria with the previous criteria is made. Moreover, an example is given to show the effectiveness of the obtained results.

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2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI)

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