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具有无界离散时变延迟的脉冲Cohen-Grossberg神经网络的稳定性分析

Stability analysis of impulsive Cohen-Grossberg neural network with unbounded discrete time-varying delays.

作者信息

Song Qiankun, Cao Jinde

机构信息

Department of Mathematics, Chongqing Jiaotong University, Chongqing 400074, China.

出版信息

Int J Neural Syst. 2007 Oct;17(5):407-17. doi: 10.1142/S012906570700124X.

DOI:10.1142/S012906570700124X
PMID:18098372
Abstract

In this paper, the impulsive Cohen-Grossberg neural network with unbounded discrete time-varying delays is considered. By using the analysis method and inequality technique, several sufficient conditions are obtained to ensure the global exponential stability of the addressed neural network. These results generalize the existing relevant stability results. Two examples with simulations are given to show the effectiveness of the obtained results.

摘要

本文考虑了具有无界离散时变延迟的脉冲Cohen-Grossberg神经网络。通过运用分析方法和不等式技巧，得到了若干确保所研究神经网络全局指数稳定性的充分条件。这些结果推广了现有的相关稳定性结果。给出了两个带有仿真的例子以说明所得结果的有效性。

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