Nothing Special   »   [go: up one dir, main page]

Skip to main content

Criteria for Exponential Stability of Cohen-Grossberg Neural Networks with Multiple Time-Varying Delays

  • Conference paper
Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence (ICIC 2008)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5227))

Included in the following conference series:

Abstract

The exponential stability is analyzed for Cohen-Grossberg neural networks with multiple time-varying delays. The boundedness, differentiability or monotonicity condition is not assumed on the activation functions. Lyapunov functional method is employed to investigate the stability of the neural networks, and general sufficient conditions for the global exponential stability are derived. A numerical example is presented to demonstrate the effectiveness of the obtained criteria.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 189.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Chen, T.P., Rong, L.B.: Delay-independent Stability Analysis of Cohen-Grossberg Neural Networks. Physics Letters A 317, 436–449 (2003)

    Article  MATH  MathSciNet  Google Scholar 

  2. Cohen, M.A., Grossberg, S.: Absolute Stability and Global Pattern Formation and Partial Memory Storage by Competitive Neural Networks. IEEE Transactions on Systems, Man and Cybernetics SMC-13, 815–826 (1983)

    MathSciNet  Google Scholar 

  3. Driver, R.D.: Ordinary and Delay Differential Equations. Springer, New York (1977)

    MATH  Google Scholar 

  4. van den Driessche, P., Zou, X.: Global Attractivity in Delayed Hopfield Neural Network Models. SIAM J. Appl. Math. 58, 1878–1890 (1998)

    Article  MATH  MathSciNet  Google Scholar 

  5. Gopalsamy, K., He, X.Z.: Stability in Asymmetric Hopfield Nets with Transmission Delays. Physica D 76, 344–358 (1994)

    Article  MATH  MathSciNet  Google Scholar 

  6. Grossberg, S.: Nonlinear Neural Networks: Principles, Mechanisms, and Architectures. Neural Networks 1, 17–61 (1988)

    Article  Google Scholar 

  7. Hwang, C.C., Cheng, C.J., Liao, T.L.: Globally Exponential Stability of Generalized Cohen-Grossberg Neural Networks with Delays. Physics Letters A 319(1-2), 157–166 (2003)

    Article  MATH  Google Scholar 

  8. Jiang, L.: Global Exponential Stability of Cohen-Grossberg Neural Networks with Time-Varying Delays. Chaos, Solitons and Fractals 26, 935–945 (2005)

    Article  MATH  MathSciNet  Google Scholar 

  9. Liao, X.F., Li, C.G., Wong, K.W.: Criteria for Exponential Stability of Cohen-Grossberg Neural Networks. Neural Networks 17, 1401–1414 (2004)

    Article  MATH  Google Scholar 

  10. Morita, M.: Associative Memory with Non-monotone Dynamics. Neural Networks 6(1), 115–126 (1993)

    Article  Google Scholar 

  11. Peng, J.G., Qiao, H., Xu, Z.B.: A New Approach to Stability of Neural Networks with Time-varying Delays. Neural Networks 15, 95–103 (2002)

    Article  Google Scholar 

  12. Tank, D.W., Hopfield, J.J.: Simple “Neural” Optimization Networks: An A/D Converter, Signal Decision Circuit, and a Linear Programming Circuit. IEEE Transactions on Circuits and Systems 33(5), 533–541 (1986)

    Article  Google Scholar 

  13. Wan, A.H., Mao, W.H., Qiao, H., Zhang, B.: Global Asymptotic Stability of Cohen-Grossberg Neural Networks with Multiple Discrete Delays. In: Huang, D.-S., Heutte, L., Loog, M. (eds.) ICIC 2007. LNCS (LNAI), vol. 4682, pp. 47–58. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  14. Wang, L., Zou, X.F.: Exponential Stability of Cohen-Grossberg Neural Networks. Neural Networks 15, 415–422 (2002)

    Article  Google Scholar 

  15. Wang, L., Zou, X.F.: Harmless Delays in Cohen-Grossberg Neural Network. Physica D 170(2), 162–173 (2002)

    Article  MATH  MathSciNet  Google Scholar 

  16. Wu, W., Cui, B.T., Lou, X.: Some Criteria for Asymptotic Stability of Cohen-Grossberg Neural Networks with Time-Varying Delays. Neurocomputing 70(4-6), 1085–1088 (2007)

    Google Scholar 

  17. Ye, H., Michel, A.N., Wang, K.: Qualitative Analysis of Cohen-Grossberg Neural Networks with Multiple Delays. Physics Review E 51, 2611–2618 (1995)

    Article  MathSciNet  Google Scholar 

  18. Zhang, Y., Tan, K.K.: Dynamic Stability for Lotka-Volterra Recurrent Neural Networks with Delays. Physical Review E 66, 011910 (2002)

    Article  MathSciNet  Google Scholar 

  19. Zhou, D.M., Cao, J.D.: Globally Exponential Stability Conditions for Cellular Neural Networks with Time-Varying Delays. Applied Mathematics and Computation 131(2-3), 487–496 (2002)

    Article  MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

De-Shuang Huang Donald C. Wunsch II Daniel S. Levine Kang-Hyun Jo

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Wan, A., Mao, W. (2008). Criteria for Exponential Stability of Cohen-Grossberg Neural Networks with Multiple Time-Varying Delays. In: Huang, DS., Wunsch, D.C., Levine, D.S., Jo, KH. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. ICIC 2008. Lecture Notes in Computer Science(), vol 5227. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85984-0_3

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-85984-0_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-85983-3

  • Online ISBN: 978-3-540-85984-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics