Search results

  1. 1.
    0389184 - ÚI 2014 RIV DE eng M - Monography Chapter
    Kainen, P.C. - Kůrková, Věra - Sanguineti, M.
    Approximating Multivariable Functions by Feedforward Neural Nets.
    Handbook on Neural Information Processing. Berlin: Springer, 2013 - (Bianchini, M.; Maggini, M.; Jain, L.), s. 143-181. Intelligent Systems Reference Library, 49. ISBN 978-3-642-36656-7
    R&D Projects: GA ČR GAP202/11/1368; GA MŠMT(CZ) ME10023
    Grant - others:CNR-AV ČR(CZ) Project 2010–2012 “Complexity of Neural-Network and Kernel Computational Models
    Institutional support: RVO:67985807
    Keywords : multivariable approximation * feedforward neural networks * network complexity * approximation rates * variational norm * best approximation * tractability of approximation
    Subject RIV: IN - Informatics, Computer Science
    Permanent Link: http://hdl.handle.net/11104/0218068
     
     
  2. 2.
    0315078 - ÚI 2009 RIV US eng J - Journal Article
    Kainen, P.C. - Kůrková, Věra - Sanguineti, M.
    Complexity of Gaussian-Radial-Basis Networks Approximating Smooth Functions.
    [Složitost Gaussovských radiálních sítí.]
    Journal of Complexity. Roč. 25, č. 1 (2009), s. 63-74. ISSN 0885-064X. E-ISSN 1090-2708
    R&D Projects: GA ČR GA201/08/1744
    Institutional research plan: CEZ:AV0Z10300504
    Keywords : Gaussian-radial-basis-function networks * rates of approximation * model complexity * variation norms * Bessel and Sobolev norms * tractability of approximation
    Subject RIV: IN - Informatics, Computer Science
    Impact factor: 1.227, year: 2009
    Permanent Link: http://hdl.handle.net/11104/0165396
     
     


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