Advertisement

Stability of Fuzzy Cellular Neural Networks with Impulses

  • Tingwen Huang
  • Marco Roque-Sol
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3971)

Abstract

In this paper, we study impulsive fuzzy cellular neural networks. Criteria are obtained for the existence and exponential stability of a unique equilibrium of fuzzy cellular neural networks impulsive state displacements at fixed instants of time.

Keywords

Equilibrium Point Exponential Stability Unique Equilibrium Cellular Neural Network Contraction Mapping Principle 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Cao, J., Wang, J., Liao, X.: Novel Stability Criteria of Delayed Cellular Neural Networks. International Journal of Neural Systems 13, 365–375 (2003)CrossRefGoogle Scholar
  2. 2.
    Gopalsamy, K.: Stability of Artificial Neural Networks with Impulses. Applied Mathematics and Computation 154, 783–813 (2004)MATHCrossRefMathSciNetGoogle Scholar
  3. 3.
    Horn, R.A., Johnson, C.R.: Topics in Matrix Analysis. Cambridge University Press, Cambridge (1999)Google Scholar
  4. 4.
    Huang, T., Zhang, L.: Exponential Stability of Fuzzy Cellular Neural Networks. In: Wang, J., Liao, X.-F., Yi, Z. (eds.) ISNN 2005. LNCS, vol. 3496, pp. 168–173. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  5. 5.
    Huang, T.: Exponential Stability of Delayed Fuzzy Cellular Neural Networks with Diffusion. to appear in Chaos, Solitons and FractralsGoogle Scholar
  6. 6.
    Huang, T.: Exponential Stability of Fuzzy Cellular Neural Networks with Unbounded Distributed Delay. to appear in Physics Letters AGoogle Scholar
  7. 7.
    Li, Y.: Global Exponential Stability of BAM Neural Networks with Delays and Impulses. Chaos, Solitons and Fractals 24, 279–285 (2005)MATHMathSciNetGoogle Scholar
  8. 8.
    Li, C., Liao, X., Zhang, R.: Impulsive Synchronization of Nonlinear Coupled Chaotic Systems. Physics Letters A 328, 47–50 (2004)MATHCrossRefMathSciNetGoogle Scholar
  9. 9.
    Liu, Y., Tang, W.: Exponential Stability of Fuzzy Cellular Neural Networks with Constant and Time-varying Delays. Physics Letters A 323, 224–233 (2004)MATHCrossRefMathSciNetGoogle Scholar
  10. 10.
    Liao, X.F., Wong, K., Li, C.: Global Exponential Stability for a Class of Generalized Neural Networks with Distributed Delays. Nonlinear Analysis: Real World Applications 5, 527–547 (2004)MATHCrossRefMathSciNetGoogle Scholar
  11. 11.
    Samoilenko, A., Perestyuk, N.: Impulsive Differential Equations. In: World Scientific Series on Nonlinear Science. Series A: Monographs and Treatises, vol. 14. World Scientific, Singapore (1995)Google Scholar
  12. 12.
    Yang, T., Yang, L.B., Wu, C.W., Chua, L.O.: Fuzzy Cellular Neural Networks: Theory. In: Proc. of IEEE International Workshop on Cellular Neural networks and Applications, pp. 181–186 (1996)Google Scholar
  13. 13.
    Yang, T., Yang, L.B., Wu, C.W., Chua, L.O.: Fuzzy Cellular Neural Networks: Applications. In: Proc. of IEEE International Workshop on Cellular Neural Networks and Applications, pp. 225–230 (1996)Google Scholar
  14. 14.
    Yang, T., Yang, L.B.: The Global Stability of Fuzzy Cellular Neural Network. Circuits and Systems I: Fundamental Theory and Applications 43, 880–883 (1996)CrossRefGoogle Scholar
  15. 15.
    Yang, X., Liao, X., Evans, D., Tnag, Y.: Existence and Stability of Periodic Solution in Impulsive Hopfield. Neural Networks with Finite Distributed Delays 343, 108–116 (2005)MATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Tingwen Huang
    • 1
  • Marco Roque-Sol
    • 2
  1. 1.Texas A&M University at QatarDohaQatar
  2. 2.Mathematics DepartmentTexas A&M UniversityCollege StationUSA

Personalised recommendations