Počet záznamů: 1

Some Comparisons of Complexity in Dictionary-Based and Linear Computational Models

  1. 1.
    0350421 - UIVT-O 2011 RIV GB eng J - Článek v odborném periodiku
    Gnecco, G. - Kůrková, Věra - Sanguineti, M.
    Some Comparisons of Complexity in Dictionary-Based and Linear Computational Models.
    Neural Networks. Roč. 24, č. 2 (2011), s. 171-182 ISSN 0893-6080
    Grant CEP: GA ČR GA201/08/1744
    Grant ostatní: CNR - AV ČR project 2010-2012(XE) Complexity of Neural-Network and Kernel Computational Models
    Výzkumný záměr: CEZ:AV0Z10300504
    Klíčová slova: linear approximation schemes * variable-basis approximation schemes * model complexity * worst-case errors * neural networks * kernel models
    Kód oboru RIV: IN - Informatika
    Impakt faktor: 2.182, rok: 2011

    We compare upper bounds on worst-case errors in variable-basis approximation with lower bounds on such errors for any linear approximator. Using methods from nonlinear approximation and integral representations tailored to computational units, we describe some cases where neural networks outperform any linear approximator.
    Trvalý link: http://hdl.handle.net/11104/0190434