Počet záznamů: 1

Evolutionary learning of regularization networks with product kernel units

  1. 1.
    0369174 - UIVT-O 2012 RIV US eng C - Konferenční příspěvek (zahraniční konf.)
    Vidnerová, Petra - Neruda, Roman
    Evolutionary learning of regularization networks with product kernel units.
    Systems, Man and Cybernetics. Piscataway: IEEE, 2011, s. 638-643. ISBN 978-1-4577-0652-3. ISSN 1062-922X.
    [SMC 2011. International Conference on Systems, Man and Cybernetics. Anchorage (US), 09.10.2011-12.10.2011]
    Grant CEP: GA ČR GAP202/11/1368; GA AV ČR KJB100300804
    Výzkumný záměr: CEZ:AV0Z10300504
    Klíčová slova: genetic algorithms * kernel functions * regularization networks
    Kód oboru RIV: IN - Informatika

    This paper deals with learning possibilities of regularization networks with product kernel units. Approximation problems formulated as regularized minimization problems with kernel-based stabilizers lead to solutions of the shape of linear combination of kernel functions. These can be expressed as one-hidden layer feed-forward neural network schemes, called regularization networks. We propose a novel evolutionary algorithm utilizing for regularization networks with product kernels. This algorithm utilizes genetic search for suitable network parameters as well as kernel functions.
    Trvalý link: http://hdl.handle.net/11104/0203304
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