Acta mathematica scientia,Series A ›› 2015, Vol. 35 ›› Issue (3): 634-640.

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Globally Asymptotic Stability of A New Class of Neutral Neural Networks with Time-Varying Delays

Luo Ricai1, Xu Honglei2, Wang Wusheng3   

  1. 1. School of Computer and Information Engineering, Hechi University, Guangxi Yizhou 546300;
    2. Department of Mathematics and Statistics, Curtin University, Perth, WA 6845, Australia;
    3. School of Mathematics and Statistics, Hechi University, Guangxi Yizhou 546300
  • Received:2014-04-29 Revised:2014-10-10 Online:2015-06-25 Published:2015-06-25

Abstract:

In this paper, we study the stability problem of a class of neural neutral network systems whose involve an activation function with differential time-delay state variables. By constructing Lyapunov functions and using LMI techniques, we obtain a sufficient condition for the global asymptotic stability of these neural networks. Finally, we demonstrate the validity of our results by use of a numerical example.

Key words: Neutral neural networks, Varying time delays, Global asymptotic stability, Sufficient condition

CLC Number: 

  • O175
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