ICANN ’93 pp 396-399 | Cite as

An Analytically Transparent Network for Sequence Recognition

  • Marc F. J. Drossaers
Conference paper


In this article technical details of a neural network for sequence recognition are presented. The network is powerful enough to simulate finite-state acceptors, while its analysis is much simplified, compared to the standard Hopfield model. Also its processing speed is optimal, and the presence of mixture states is externally controllable. The network is robust under synaptic noise, it has error correcting properties and it can recover from gross input errors.


Input Image External Input Sequence Recognition Temporal Image Mixture State 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [1]
    D.J. Amit. Proc. Natl. Acad. Sci. USA, 85: 2141–2145, 1988.MathSciNetCrossRefGoogle Scholar
  2. [2]
    D.J. Amit, H. Gutfreund, and H. Sompolinsky. Physical Review A, 32(2):1007–1018, 1985.MathSciNetCrossRefGoogle Scholar
  3. [3]
    J. Buhmann, R. Divko, and K. Schulten. Physical Review A, 39(5): 2689–2692, 1989.MathSciNetCrossRefGoogle Scholar
  4. [4]
    E. Domany, J.L. van Hemmen, and K. Schulten. Models of Neural Networks. Springer, Berlin, 1991.CrossRefMATHGoogle Scholar
  5. [5]
    M.F.J. Drossaers. In Proceedings of COLING’ 92, pages 113–119, 1992.Google Scholar
  6. [6]
    J.J. Hopfield. Proc. Natl. Acad. Sci. USA, 79: 2554–2558, 1982.Google Scholar
  7. [7]
    D. Kleinfeld. Proc. Natl. Acad. Sci. USA, 83: 9469–9473, 1986.Google Scholar
  8. [8]
    H. Moisl. Connection Science, 4(2): 67–91, 1992.CrossRefGoogle Scholar
  9. [9]
    D. Servan-Schreiber, A. Cleeremans, and J.L. McClelland. In D.S. Touretzky, editor, Advances in Neural Information Processing systems I, Los Altos (Cal.), 1989. Morgan Kaufmann.Google Scholar
  10. [10]
    H. Sompolinsky and I. Kanter. Physical Review Letters, 57(22): 2861–2864, 1986.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag London Limited 1993

Authors and Affiliations

  • Marc F. J. Drossaers
    • 1
  1. 1.Computer Science Dept.University of TwenteEnschedeThe Netherlands

Personalised recommendations