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A novelty detector using a network of integrate and fire neurons

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

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

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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.

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References

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Author information

Authors and Affiliations

  1. Dept. de Génie Informatique, Ecole Polytechnique de Montréal, Canada, Canada

    Tuong Vinh Ho

  2. Dept. Des Sciences Appliquées, Université du Québec á Chicoutimi, Canada, Canada

    Tuong Vinh Ho & Jean Rouat

Authors
  1. Tuong Vinh Ho
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  2. Jean Rouat
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Editor information

Wulfram Gerstner Alain Germond Martin Hasler Jean-Daniel Nicoud

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© 1997 Springer-Verlag Berlin Heidelberg

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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

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

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63631-1

  • Online ISBN: 978-3-540-69620-9

  • eBook Packages: Springer Book Archive

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