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

Authors:
Jin-Liang Shao;Ting-Zhu Huang;Sheng Zhou
Affiliations:
School of Applied Mathematics, University of Electronic Science and Technology of China, Chengdu, People's Republic of China 610054;School of Applied Mathematics, University of Electronic Science and Technology of China, Chengdu, People's Republic of China 610054;School of Applied Mathematics, University of Electronic Science and Technology of China, Chengdu, People's Republic of China 610054
Venue:
Neural Processing Letters
Year:
2009

Citing 12
Cited 2

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Abstract

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.