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On Tractability of Neural-Network Approximation

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Adaptive and Natural Computing Algorithms (ICANNGA 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5495))

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Abstract

The tractability of neural-network approximation is investigated. The dependence of worst-case errors on the number of variables is studied. Estimates for Gaussian radial-basis-function and perceptron networks are derived.

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Author information

Authors and Affiliations

  1. Department of Mathematics, Georgetown University, Washington, D.C., 20057-1233, USA

    Paul C. Kainen

  2. Institute of Computer Science, Academy of Sciences of the Czech Republic, Pod Vodárenskou věží  2, Prague 8, Czech Republic

    Věra Kůrková

  3. Department of Communications, Computer, and System Sciences (DIST), University of Genoa, Via Opera Pia 13, 16145, Genova, Italy

    Marcello Sanguineti

Authors
  1. Paul C. Kainen
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  2. Věra Kůrková
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  3. Marcello Sanguineti
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Editor information

Editors and Affiliations

  1. Department of Environmental Sciences, University of Kuopio, PO Box 1627, FIN-70211, Kuopio, Finland

    Mikko Kolehmainen

  2. Department of Computer Science, University of Kuopio, P.O.Box 1627, 70211, Kuopio, Finland

    Pekka Toivanen

  3. Institute of Control and Industrial Electronics, Warsaw University of Technology, ul. Koszykowa 75, 00-662, Warszawa, Poland

    Bartlomiej Beliczynski

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Kainen, P.C., Kůrková, V., Sanguineti, M. (2009). On Tractability of Neural-Network Approximation. In: Kolehmainen, M., Toivanen, P., Beliczynski, B. (eds) Adaptive and Natural Computing Algorithms. ICANNGA 2009. Lecture Notes in Computer Science, vol 5495. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04921-7_2

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  • DOI: https://doi.org/10.1007/978-3-642-04921-7_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04920-0

  • Online ISBN: 978-3-642-04921-7

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