Skip to main content

Dynamics of Neural Networks with Delay: Attractors and Content-Addressable Memory

  • Chapter
  • 543 Accesses

Part of the book series: Mathematics and Its Applications ((MAIA,volume 528))

Abstract

In the design of a neural network, either for biological modeling, cognitive simulation, numerical computation or engineering applications, it is important to describe the dynamics of the network. The success in this area in the early 1980’s was one of the main sources for the resurgence of interest in neural networks, and the current progress towards understanding neural dynamics has been part of exhaustive efforts to lay down a solid theoretical foundation for this fast growing theory and for the applications of neural networks.

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   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
Hardcover Book
USD   109.99
Price excludes VAT (USA)
  • Durable hardcover 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. Babcock, K.L. and Westevelt, R.M., Dynamics of simple electronic neural networks, Physica D, 28, 1987, 305–316.

    Article  MathSciNet  Google Scholar 

  2. Baldi, P. and Attyia, A.F., How delays effect neural dynamics and learning, IEEE Trans. Neural Networks, 5, 1994, 612–621.

    Article  Google Scholar 

  3. Baptistini, M.Z. and Tdboas, P.Z., On the existence and global bifurcation of periodic solutions to planar differential delay equations, J. Differential Equations, 127, 1996, 391–425.

    Article  MathSciNet  MATH  Google Scholar 

  4. Bélair, J., Campbell, S.A., and van den Driessche, P., Frustration, stability and delay-induced oscillations in a neural network model, SIAM J. Appl. Math., 46, 1996, 245–255.

    Article  Google Scholar 

  5. Cao, J. and Zhou, D., Stability analysis of delayed cellular neural networks, Neural Networks, 11, 1998, 1601–1605.

    Article  Google Scholar 

  6. Chen, Y., Krisztin, T., and Wu, J., Connecting orbits from synchronous periodic solutions to phase-locked periodic solutions in a delay differential system, J. Differential Equations, 1999, to appear.

    Google Scholar 

  7. Chen, Y. and Wu, J., Existence and attraction of a phase-locked oscillation in a delayed network of two neurons, Advances in Differential Equations, 1998, to appear.

    Google Scholar 

  8. Chen, Y. and Wu, J., Minimal instability and unstable set of a phase-locked periodic orbit in a delayed neural network, Physics D, 134, 1999a, 185–199.

    Article  MATH  Google Scholar 

  9. Chen, Y. and Wu, J., The asymptotic shapes of periodic solutions of a singular delay differential system, J. Differential Equations, 1999b, to appear.

    Google Scholar 

  10. Chen, Y. and Wu, J., Slowly oscillating periodic solutions in a delayed frustrated network of two neurons, 1999c, preprint.

    Google Scholar 

  11. Chua, L.O. and Yang, L., Cellular neural networks: Theory, IEEE Trans. Circuits Syst. I, 35, 1988, 1257–1272.

    Article  MathSciNet  Google Scholar 

  12. Cohen, M.A. and Grossberg, S., Absolute stability of global pattern formation and parallel memory storage by competitive neural networks, IEEE Transactions on Systems, Man, and Cybernetics, 13, 1983, 815–826.

    MathSciNet  MATH  Google Scholar 

  13. Fiedler, B. and Gedeon, T., A class of convergence neural network dynamics, Physica D, 111, 1998, 288–294.

    Article  MathSciNet  MATH  Google Scholar 

  14. Gedeon, T., Structure and dynamics of artificial neural networks, in Fields Institute Communications: Differential Equations with Applications to Biology, (S. Ruan, G. Wolkowicz, and J. Wu, eds.), Vol. 21, 1999, 217–224.

    Google Scholar 

  15. Giannakopoulos, F. and Zapp, A., Local and global Hopf bifurcation in a scalar delay differential equation, 1998, preprint.

    Google Scholar 

  16. Gilli, Strange attractors in delayed cellular neural networks, IEEE Trans. Circuits Syst., 40, 1993, 849–853.

    Article  Google Scholar 

  17. Gopalsamy, K. and He, X.-Z., Stability in asymmetric Hopfield nets with transmission delays, Physica D, 76, 1994, 344–358.

    Article  MathSciNet  MATH  Google Scholar 

  18. Hebb, D.O., The Organization of Behavior, John Wiley & Sons, New York, 1949.

    Google Scholar 

  19. Herz, A.V.M., Salzer, B., Kühn, R., and van Hemmen, J.L., Hebbian learning reconsidered: Representation of static and dynamic objects in associative neural nets, Biol. Cybem., 60, 1989, 457–467.

    Article  MATH  Google Scholar 

  20. Hirsch, M., Stability and convergence in strongly monotone dynamical systems, J. Reine Angew. Math., 383, 1988, 1–53.

    Article  MathSciNet  MATH  Google Scholar 

  21. Hopfield, J.J., Neurons with graded response have collective computational properties like those of two-state neurons, Proc. Natl. Acad. Sci., 81, 1984, 3088–3092.

    Article  Google Scholar 

  22. Huang, L. and Wu, J., Joint effects of the threshold and synaptic delay on dynamics of artificial neural networks with McCulloch-Pitts nonlinearity, 1999a, preprint.

    Google Scholar 

  23. Huang, L. and Wu, J., The role of threshold in preventing delay-induced oscillations of frustrated neural networks with McCulloch-Pitts nonlinearity, 1999b, preprint.

    Google Scholar 

  24. Krisztin, T. and Walther, H.-O., Unique periodic orbits for delayed positive feedback and the global attractor, J. Dynamics and Differential Equations, 1999, to appear.

    Google Scholar 

  25. Krisztin, T., Walther, H.-O., and Wu, J., Shape, Smoothness and Invariant Stratification of an Attracting Set for Delayed Monotone Positive Feedback, the Fields Institute Monographs Series 11, Amer. Math. Soc., Rhode Island, 1999.

    MATH  Google Scholar 

  26. Levine, D.S., Introduction to Neural and Cognitive Modelling, Lawrence Erlbaum Associate, Inc., New Jersey, 1991.

    Google Scholar 

  27. Marcus, C.M. and Westervelt, R.M., Basins of attraction for electronic neural networks, in Neural Information Processing Systems, (D.Z. Anderson, ed.) American Institute of Physics, New York, 1988, 524–533.

    Google Scholar 

  28. Marcus, C.M. and Westervelt, R.M., Stability of analog neural networks with delay, Physical Review A, 39, 1989, 347–359.

    Article  MathSciNet  Google Scholar 

  29. May, R.M. and Leonard, W.J., Nonlinear aspects of competition between three species, SIAM J. Appl. Math., 29, 1975, 243–253.

    MathSciNet  MATH  Google Scholar 

  30. Müller, B. and Reinhardt, J., Neural Networks, An Introduction, Springer-Verlag, Berlin, 1991.

    Google Scholar 

  31. Olien, L. and Bélair, J., Bifurcation’s, stability, and monotonically properties of a delayed neural network model, Physica D, 102, 1997, 349–363.

    Article  MathSciNet  MATH  Google Scholar 

  32. Pakdaman, K., Grotta-Ragazzo, C.P., Malta, K., and Vibert, J.-F., Delay-induced transient oscillations in a two-neuron network, Resends, 1997, 45–54.

    Google Scholar 

  33. Pakdaman, K., Grotta-Ragazzo, C.P., Malta, C.P., Rain, O., and Vibert, J.-F., Effect of delay on the boundary of the basin of attraction in a system of two neurons, Neural Networks, 11, 1998, 509–519.

    Article  Google Scholar 

  34. Ruan, S. and Wei, J., Periodic solutions of planar systems with two delays, Proc. Royal Soc. Edinburgh (A), 129, 1999, 1017–1032.

    MathSciNet  MATH  Google Scholar 

  35. Smith, H.L., Monotone semiflows generated by functional differential equations, J. Differential Equations, 66, 1987, 420–442.

    Article  MathSciNet  MATH  Google Scholar 

  36. Smith, H.L., Convergent and oscillatory activation dynamics for cascades of neural nets with nearest neighbor competitive or cooperative interactions, Neural Networks, 4, 1991, 41–46.

    Article  Google Scholar 

  37. van den Driessche, P. and Zou, X.F., Global attractivity in delayed Hopfield neural networks models, SIAM J. Appl. Math., 58, 1998, 1878–1890.

    Article  MathSciNet  MATH  Google Scholar 

  38. Walther, H.-O., The singularities of an attractor of a delay differential equation, Functional Differential Equations, 5, 1998, 513–548.

    MathSciNet  MATH  Google Scholar 

  39. Wu, J., Symmetric functional differential equations and neural networks with memory, Trans. Amer. Math. Soc., 350, 1998, 4799–4838.

    Article  MathSciNet  MATH  Google Scholar 

  40. Wu, J., Introduction to Neural Dynamics and Signal Delays, 1999, preprint.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2001 Kluwer Academic Publishers

About this chapter

Cite this chapter

Wu, J. (2001). Dynamics of Neural Networks with Delay: Attractors and Content-Addressable Memory. In: Vajravelu, K. (eds) Differential Equations and Nonlinear Mechanics. Mathematics and Its Applications, vol 528. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-0277-3_28

Download citation

  • DOI: https://doi.org/10.1007/978-1-4613-0277-3_28

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-0-7923-6867-0

  • Online ISBN: 978-1-4613-0277-3

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics