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Exponential Stability of Interval Neural Networks with Variable Delays

  • Jiye Zhang
  • Dianbo Ren
  • Weihua Zhang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4113)

Abstract

In this paper, the conditions ensuring existence, uniqueness, and global exponential stability of the equilibrium point of interval neural networks with variable delays are studied. Applying idea of vector Liapunov function, the sufficient conditions for global exponential stability of interval neural networks are obtained.

Keywords

Neural Network Equilibrium Point Exponential Stability Variable Delay Cellular Neural Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Chua, L.O., Yang, L.: Cellular Neural Networks: Theory. IEEE Trans. Circ. Syst. 35, 1257–1272 (1988)zbMATHCrossRefMathSciNetGoogle Scholar
  2. 2.
    Forti, M., Tesi, A.: New Conditions for Global Stability of Neural Networks with Application to Linear and Quadratic Programming Problems. IEEE Trans. Circ. Syst. I 42, 354–366 (1995)zbMATHCrossRefMathSciNetGoogle Scholar
  3. 3.
    Van Den Driessche, P., Zou, X.: Global Attractivity in Delayed Hopfield Neural Networks Models. SIAM J. Appl. Math. 58, 1878–1890 (1998)zbMATHCrossRefMathSciNetGoogle Scholar
  4. 4.
    Arik, S., Tavanoglu, V.: On the Global Asymptotic Stability of Delayed Cellular Neural Networks. IEEE Trans. Circ. Syst. I 47, 571–574 (2000)zbMATHCrossRefGoogle Scholar
  5. 5.
    Zhang, J., Jin, X.: Global Stability Analysis in Delayed Hopfield Neural Networks Models. Neural Networks 13, 745–753 (2000)CrossRefGoogle Scholar
  6. 6.
    Zhang, J.: Absolutely Exponential Stability in Delayed Cellular Neural Networks. Int. J. Circ. Theor. Appl. 30, 395–409 (2002)zbMATHCrossRefGoogle Scholar
  7. 7.
    Zhang, J.: Globally Exponential Stability of Neural Networks with Variable Delays. IEEE Trans. Circ. Syst. 50, 288–291 (2003)Google Scholar
  8. 8.
    Chen, T.: Global Exponential Stability of Delayed Hopfield Neural Networks. Neural Networks 14, 977–980 (2001)CrossRefGoogle Scholar
  9. 9.
    Liao, X., Wong, K.W., Wu, Z., Chen, G.: Novel Robust Stability Criteria for Interval Delayed Hopfield Neural Networks. IEEE Trans. Circ. Syst. I 48, 1355–1359 (2001)zbMATHCrossRefMathSciNetGoogle Scholar
  10. 10.
    Siljak, D.D.: Large-Scale Dynamic Systems-Stability and Structure. Elsevier, New York (1978)zbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Jiye Zhang
    • 1
  • Dianbo Ren
    • 1
  • Weihua Zhang
    • 1
  1. 1.National Traction Power LaboratorySouthwest Jiaotong UniversityChengduPeople’s Republic of China

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