Global Asymptotic Robust Stability and Global Exponential Robust Stability of Neural Networks with Time-Varying Delays

作者:Jin-Liang Shao, Ting-Zhu Huang, Sheng Zhou

摘要

In this paper, based on nonnegative matrix theory, the Halanay’s inequality and Lyapunov functional, some novel sufficient conditions for global asymptotic robust stability and global exponential robust stability of neural networks with time-varying delays are presented. It is shown that our results improve and generalize several previous results derived in the literatures. From the obtained results, some linear matrix inequality criteria are derived. Finally, a simulation is given to show the effectiveness of the results.

论文关键词:Neural networks, Time-varying delays, Global robust stability

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论文官网地址:https://doi.org/10.1007/s11063-009-9120-6