中国物理B ›› 2012, Vol. 21 ›› Issue (4): 40701-040701.doi: 10.1088/1674-1056/21/4/040701

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邱芳1 2,张全信1 2,邓学辉1   

  • 收稿日期:2011-08-12 修回日期:2011-10-23 出版日期:2012-02-29 发布日期:2012-02-29
  • 通讯作者: 邱 芳, E-mail:rgbayqf@yahoo.com.cn E-mail:rgbayqf@yahoo.com.cn

Further improvement of the Lyapunov functional and the delay-dependent stability criterion for a neural network with a constant delay

Qiu Fang(邱芳) a)b)†, Zhang Quan-Xin(张全信)a)b), and Deng Xue-Hui(邓学辉) a)   

  1. a. Department of Mathematics and Information Science, Binzhou University, Binzhou 256603, China;
    b. Insititute of Differential Equation and Dynamical System, Binzhou University, Binzhou 256603, China
  • Received:2011-08-12 Revised:2011-10-23 Online:2012-02-29 Published:2012-02-29
  • Contact: Qiu Fang, E-mail:rgbayqf@yahoo.com.cn E-mail:rgbayqf@yahoo.com.cn
  • Supported by:
    Project supported by the Promotive Research Fund for Young and Middle-Aged Scientists of Shandong Province of China(Grant No.BS2010SF001),Research Fund for the Doctors of Binzhou University(Grant No.2010Y09),and the Natural ScienceFoundation of Shandong Province of China(Grant No.ZR2010AM031)

Abstract: This paper investigates the asymptotical stability problem of a neural system with a constant delay. A new delay-dependent stability condition is derived by using the novel augmented Lyapunov-Krasovskii function with triple integral terms, and the additional triple integral terms play a key role in the further reduction of conservativeness. Finally, a numerical example is given to demonstrate the effectiveness and lower conservativeness of the proposed method.

Key words: neural system, globally asymptotical stability, time delay

中图分类号:  (Neural networks, fuzzy logic, artificial intelligence)

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