混合脉冲和切换神经网络

IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics Pub Date : 2008-12-01 DOI:10.1109/TSMCB.2008.928233

Chuandong Li, G. Feng, Tingwen Huang

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引用次数: 104

摘要

本文建立并研究了一种脉冲和开关混合Hopfield神经网络模型。利用切换Lyapunov函数和广义Halanay不等式，建立了具有任意条件脉冲切换的神经网络的渐近稳定性和指数稳定性的一般准则，以聚合形式描述了脉冲和切换效应。给出了几个数值算例来说明和解释理论结果。

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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On Hybrid Impulsive and Switching Neural Networks

This paper formulates and studies a model of hybrid impulsive and switching Hopfield neural networks (NNs). Using switching Lyapunov functions and a generalized Halanay inequality, some general criteria, which characterize the impulse and switching effects in aggregated form, for asymptotic and exponential stability of such NNs with arbitrary and conditioned impulsive switching are established. Several numerical examples are given for illustration and interpretation of the theoretical results.

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来源期刊

IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics 工程技术-计算机：控制论

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审稿时长

6.0 months