Robust stability for neural networks of neutral-type with mixed time-delays

Qingyu Zhu, Wuneng Zhou, Xiaozheng Mou
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Abstract

In this paper, the robust stability is investigated for neural networks of neutral-type with both discrete and distributed time-varying delays. Based on Lyapunov-Krasovskii stability theory and stochastic analysis approaches, several new criteria are derived to guarantee the robust stability of the system. Some numerical examples are given to demonstrate the applicability of our proposed stability criteria.
混合时滞中性型神经网络的鲁棒稳定性
研究了具有离散时变时滞和分布时变时滞的中立型神经网络的鲁棒稳定性问题。基于Lyapunov-Krasovskii稳定性理论和随机分析方法,导出了保证系统鲁棒稳定性的几个新准则。通过数值算例验证了稳定性准则的适用性。
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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