Skip to main content
SpringerLink
Log in

New Criteria of Global Exponential Stability for a Class of Generalized Neural Networks with Time-Varying Delays

  • Conference paper
Book cover Advances in Neural Networks - ISNN 2006 (ISNN 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3971))

Included in the following conference series:

  • 367 Accesses

Abstract

In this paper, we essentially drop the requirement of Lipschitz condition on the activation functions. By employing Lyapunov functional and several new inequalities, some new criteria concerning global exponential stability for a class of generalized neural networks with time-varying delays are obtained, which only depend on physical parameters of neural networks. Since these new criteria do not require the activation functions to be differentiable, bounded or monotone nondecreasing and the connection weight matrices to be symmetric, they are mild and more general than previously known criteria.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

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.

References

  1. Arik, S., Tavanoglu, V.: Equilibrium Analysis of Delayed CNNs. IEEE Trans. Circuits syst. I. 45(2), 168–171 (1998)

    Article  Google Scholar 

  2. Liang, J.L., Cao, J.D.: Global Asymptotic Stability of Bi-Directional Associative Memory Networks with Distributed Delays. Applied Mathematics and Computation 152(2), 415–424 (2004)

    Article  MATH  MathSciNet  Google Scholar 

  3. Zeng, Z.G., Wang, J., Liao, X.X.: Global Asymptotic Stability and Global Exponential Stability of Neural Networks with Unbounded Time-varying Delays. IEEE Trans. on Circuits and System II. 52(3), 168–173 (2005)

    Article  Google Scholar 

  4. Ensari, T., Arik, S.: Global Stability of a Class of Neural Networks with Time-varying Delay. IEEE Trans. on Circuits And System Ii. 52(3), 126–130 (2005)

    Article  Google Scholar 

  5. Feng, C.H., Plamondon, R.: On the Stability of Delay Neural Networks System. Neural Networks 14, 1181–1118 (2001)

    Google Scholar 

  6. Zhang, Q., Ma, R.N., Wang, C., Xu, J.: On the Global Stability of Delayed Neural Networks. IEEE Trans. On Automatic Control. 48(5), 794–797 (2003)

    Article  MathSciNet  Google Scholar 

  7. Zhang, H.G., Wang, G.: Global Exponential Stability of a Class of Generalized Neural Networks with Variable Coefficients and Distributed Delays. In: Huang, D.-S., Zhang, X.-P., Huang, G.-B. (eds.) ICIC 2005. LNCS, vol. 3644, pp. 807–817. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Information Science and Engineering, Northeastern University, Shenyang, Liaoning, 110004, People’s Republic of China

    Gang Wang, Hua-Guang Zhang & Chong-Hui Song

Authors
  1. Gang Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hua-Guang Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Chong-Hui Song
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  2. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

  3. Department of Electrical Engineering, University of Louisville, 40292, Louisville, KY, U.S.A

    Jacek M. Zurada

  4. Laboratory for Computational Biology, Shanghai Center for Systems Biomedicine, 800 Dong Chuan Rd., 200240, Shanghai, China

    Bao-Liang Lu

  5. School of Electrical and Electronic Engineering, University of Manchester, UK

    Hujun Yin

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Wang, G., Zhang, HG., Song, CH. (2006). New Criteria of Global Exponential Stability for a Class of Generalized Neural Networks with Time-Varying Delays. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3971. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11759966_19

Download citation

  • DOI: https://doi.org/10.1007/11759966_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34439-1

  • Online ISBN: 978-3-540-34440-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation