Skip to main content

Exponential Synchronization of Coupled Stochastic and Switched Neural Networks with Impulsive Effects

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8866))

Abstract

In this paper, we investigate the exponential synchronization of coupled stochastic and switched neural networks (CSSNNs) with mixed time-varying delays. By exerting impulsive controller to the considered dynamical systems in each switching interval, and combining the multiple Lyapunov theory, we obtain a class of sufficient exponential synchronization criteria in terms of nonlinear equations and LMIs, which are easy to check. A simple example is presented to show the application of the criteria obtained in this paper.

This work was supported by the National Natural Science Foundation of China under grant 61272530, the Natural Science Foundation of Jiangsu Province of China under grant BK2012741, the Specialized Research Fund for the Doctoral Program of Higher Education under Grant 20130092110017, the JSPS Innovation Program under Grant CXZZ13\(_{-}\)00, and the Natural Science Foundation of the Jiangsu Higher Education Institutions under Grant 14KJB110019.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
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

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Chen, G.R., Zhou, J., Liu, Z.R.: Global synchronization of coupled delayed neural networks and applications to chaotic CNN models. Int. J. Bifurcat. Chaos 14, 2229–2240 (2004)

    Article  MATH  MathSciNet  Google Scholar 

  2. Chang, C.L., Fan, K.W., Chung, I.F., Lin, C.H.: A recurrent fuzzy coupled cellular neural network system with automatic structure and template learning. IEEE Trans. Circuits Syst. Express Briefs 53, 602–606 (2006)

    Article  Google Scholar 

  3. Liang, J.L., Wang, Z.D., Liu, Y.Y., Liu, X.H.: Robust synchronization of an array of coupled stochastic discrete-time delayed neural networks. IEEE Trans. Neural Netw. 19, 1910–1921 (2008)

    Article  Google Scholar 

  4. Wu, W., Chen, T.P.: Global synchronization criteria of linearly coupled neural network systems with time-varying coupling. IEEE Trans. Neural Netw. 19, 319–332 (2008)

    Article  Google Scholar 

  5. Cao, J.D., Chen, G.R., Li, P.: Global synchronization in an array of delayed neural networks with hybrid coupling. IEEE Trans. Syst. Man Cybern B 38(2), 488–498 (2008)

    Article  MathSciNet  Google Scholar 

  6. Yang, X.S., Cao, J.D., Long, Y., Rui, W.G.: Adaptive lag synchronization for competitive neural networks with mixed delays and uncertain hybrid perturbations. IEEE Trans. Neural Netw. 21, 1656–1667 (2010)

    Article  Google Scholar 

  7. Wu, Z.G., Shi, P., Su, H., Chu, J.: Exponential synchronization of neural networks with discrete and distributed delays under time-varying sampling. IEEE Trans. Neural Netw. Learn Syst. 23, 1368–1376 (2012)

    Article  Google Scholar 

  8. Wang, G., Shen, Y.: Exponential synchronization of coupled memristive neural networks with time delays. Neural Comput. Appl. 24, 1421–1430 (2014)

    Article  Google Scholar 

  9. Tang, Y., Fang, J.A., Miao, Q.Y.: Synchronization of stochastic delayed neural networks with Marokovian switching and its application. Int. J. Neural Syst. 19, 43–56 (2009)

    Article  Google Scholar 

  10. Lu, J.Q., Ho, D.W.C., Cao, J.D., Kurths, J.: Exponential synchronization of linearly coupled neural networks with switching topology. IEEE Trans. Neural Netw. 22, 169–175 (2011)

    Google Scholar 

  11. Shi, G.D., Ma, Q.: Synchronization of stochastic Markovian jump neural networks with reaction-diffusion terms. Neurocomputing 77, 275–280 (2012)

    Article  MathSciNet  Google Scholar 

  12. Guan, Z.H., Hill, D.J., Shen, X.: On hybrid impulsive and switching systems and application to nonlinear control. IEEE Trans. Autom. Control 50, 1058–1062 (2005)

    Article  MathSciNet  Google Scholar 

  13. Li, C.D., Feng, G., Huang, T.: On hybrid impulsive and switching neural networks. IEEE Trans. Syst. Man Cybern B Cybern 38, 1549–1560 (2008)

    Google Scholar 

  14. Zhang, W.B., Tang, Y., Miao, Q.Y., Du, W.: Exponential synchronization of coupled switched neural networks with mode-dependent impulsive effects. IEEE Trans. Neural Netw. Learn Syst. 24, 1368–1376 (2013)

    Article  Google Scholar 

  15. Wang, J.Y., Feng, J.W., Chen, X., Zhao, Y.: Cluster synchronization of nonlinearly-coupled complex networks with nonidentical nodes and asymmetrical coupling matrix. Nonlinear Dyn. 67, 1635–1646 (2012)

    Article  MATH  Google Scholar 

  16. Haykin, S.: Neural Networks. Prentice-Hall, Englewood Cliffs (1994)

    MATH  Google Scholar 

  17. Cao, J.D., Liang, J.L., Lam, J.: Exponential stability of high-order bidirectional associative memory neural networks with time delays. Physica D 199, 425–436 (2004)

    Article  MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yangling Wang .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Wang, Y., Cao, J. (2014). Exponential Synchronization of Coupled Stochastic and Switched Neural Networks with Impulsive Effects. In: Zeng, Z., Li, Y., King, I. (eds) Advances in Neural Networks – ISNN 2014. ISNN 2014. Lecture Notes in Computer Science(), vol 8866. Springer, Cham. https://doi.org/10.1007/978-3-319-12436-0_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-12436-0_9

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-12435-3

  • Online ISBN: 978-3-319-12436-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics