JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2010, Vol. 40 ›› Issue (4): 53-56.

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A new delay-dependent global asymptotic stability forneural networks with time-varying delays

LIU Guo-cai, LIU Yu-chang, JU Pei-jun   

  1. Department of Mathematics and System Science, Taishan University, Tai’an 271021, China
  • Received:2009-12-16 Online:2010-08-16 Published:2009-12-16

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Abstract:

The asymptotic stability of neural networks with time-varying delays was studied. By the use of the Lyapunov-Krasovskii functional and integralequality approach, sufficient conditions were developed to ensure that the delayed neural network has a unique equilibrium point and global asymptotic stability. Monotone was not required by the activation function, and the delayderivative could be 1 or more than 1. Reduced conservativeness of the proposed method was verified with an example.
 

Key words: global asymptotic stability, linear matrix inequality, neural network, integral-equality approach

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