[go: up one dir, main page]

Skip to main content

A novelty detector using a network of integrate and fire neurons

  • Part I: Coding and Learning in Biology
  • Conference paper
  • First Online:
Artificial Neural Networks — ICANN'97 (ICANN 1997)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1327))

Included in the following conference series:

Abstract

Information in the nervous system has often been considered as being represented by simultaneous discharges of a large set of neurons. We propose a learning mechanism for neural information processing in a simulated cortex model. Also, a new paradigm for pattern recognition by oscillatory neural networks is proposed. The relaxation time of the oscillatory networks is used as a criterion for novelty detection.

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

Access this chapter

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Dayhoff J.E. et al.: “Developing Multiple Attractors in a Recurrent Neural Networks”, Proc. of WCCN'94, San Diego, Jun. 1994, Vol. 4, pp. 710–715.

    Google Scholar 

  2. Yukio Hayashi: “Oscillatory Neural Networks and Learning of Continuously Transformed Patterns”, Neural Networks, 1994, Vol. 7, No 2, pp. 219–231.

    Google Scholar 

  3. Hill S., Villa A.: “Global Spatiotemporal Activity Influenced by Local Kinetics in a Simulated «Cortical” Neural Network, Workshop on Supercomputing in Brain Research: from topography to neural networks, 1995, World Scientific, pp. 371–375.

    Google Scholar 

  4. Matsuno Tet al.: “Periodic Signal Learning and Recognition in Coupled Oscillators”, Journal of Physical Society of Japan, Vol. 63, No. 3, March, 1994, pp. 1194–1204.

    Google Scholar 

  5. Stassinopoulos D., Bak P.: “Self-organization in a Simple Brain Model”, Proc. of WCNN'94, San Diego, Jun, 1994, Vol. 1, pp. 4–26.

    Google Scholar 

  6. Thiran P., Hasler M: “Information storage using stable and unstable oscillations: an overview”, Int. Journal of Circuit Theory and Applications, Vol. 24, 57–67, 1996.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Wulfram Gerstner Alain Germond Martin Hasler Jean-Daniel Nicoud

Rights and permissions

Reprints and permissions

Copyright information

© 1997 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Ho, T.V., Rouat, J. (1997). A novelty detector using a network of integrate and fire neurons. In: Gerstner, W., Germond, A., Hasler, M., Nicoud, JD. (eds) Artificial Neural Networks — ICANN'97. ICANN 1997. Lecture Notes in Computer Science, vol 1327. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0020140

Download citation

  • DOI: https://doi.org/10.1007/BFb0020140

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63631-1

  • Online ISBN: 978-3-540-69620-9

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics