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Efficient Pattern Discrimination with Inhibitory WTA Nets

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Artificial Neural Networks — ICANN 2001 (ICANN 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2130))

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Abstract

A mathematical analysis of a special class of winner-take-all networks is given. Starting with a solution in closed form describing the dynamics of the network, we show that an inhibitory winner-take-all net efficiently discriminates input patterns with respect to a canonical measure. This result in combination with further properties suggests an upgrading of the system by incorporating fault tolerance and efficiently generated evidential response into the system.

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Author information

Authors and Affiliations

  1. Dept. of Computer Science, Technical University, Berlin, Germany

    Brijnesh J. Jain & Fritz Wysotzki

Authors
  1. Brijnesh J. Jain
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  2. Fritz Wysotzki
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Editor information

Editors and Affiliations

  1. Dept. of Mecidal Cybernetics and Artificial Intelligence, University of Vienna, Freyung 6/2, 1010, Vienna, Austria

    Georg Dorffner

  2. Institute for Computer Aided Automation Pattern Recognition and Image Processing Group, Technical University of Vienna, Favoritenstr. 9/1832, 1040, Vienna, Austria

    Horst Bischof

  3. Institut für Statistik, Wirtschaftsuniversität Wien, Augasse 2-6, 1090, Wien, Austria

    Kurt Hornik

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© 2001 Springer-Verlag Berlin Heidelberg

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Jain, B.J., Wysotzki, F. (2001). Efficient Pattern Discrimination with Inhibitory WTA Nets. In: Dorffner, G., Bischof, H., Hornik, K. (eds) Artificial Neural Networks — ICANN 2001. ICANN 2001. Lecture Notes in Computer Science, vol 2130. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44668-0_115

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  • DOI: https://doi.org/10.1007/3-540-44668-0_115

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42486-4

  • Online ISBN: 978-3-540-44668-2

  • eBook Packages: Springer Book Archive

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