具有比例时滞的脉冲复值神经网络的全局指数稳定性

2019 China-Qatar International Workshop on Artificial Intelligence and Applications to Intelligent Manufacturing (AIAIM) Pub Date : 2019-01-01 DOI:10.1109/AIAIM.2019.8632781

Zhenjiang Zhao, Q. Song

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引用次数: 1

摘要

本文讨论了一类具有比例时滞的脉冲复值神经网络的稳定性问题。通过选择一个合适的向量Lyapunov函数，利用不等式技巧和m矩阵理论，导出了神经网络全局指数稳定的充分条件。

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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Global Exponential Stability of Impulsive Complex-Valued Neural Networks with Proportional Delays

In this thesis, stability for a class of impulsive complex-valued neural networks with proportional time delay is discussed. By adhibiting an advisable vector Lyapunov function, making use of inequality craftsmanship and M-matrix theory, a sufficient condition is educed to insure the global exponential stability of the considered neural networks.

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来源期刊

2019 China-Qatar International Workshop on Artificial Intelligence and Applications to Intelligent Manufacturing (AIAIM)

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