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    ESANN
    2003
    111views Neural Networks» more  ESANN 2003»
    On the weight dynamics of recurrent learning
    13 years 9 months ago
    On the weight dynamics of recurrent learning
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    We derive continuous-time batch and online versions of the recently introduced efficient O(N2 ) training algorithm of Atiya and Parlos [2000] for fully recurrent networks. A mathem...
    Ulf D. Schiller, Jochen J. Steil
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    ESANN
    2003
    85views Neural Networks» more  ESANN 2003»
    Developmental pruning of synapses and category learning
    13 years 9 months ago
    Developmental pruning of synapses and category learning
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    After an initial peak, the number of synapses in mammalian cerebral cortex decreases in the formative period and throughout adult life. However, if synapses are taken to reflect ci...
    Roberto Viviani, Manfred Spitzer
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    ESANN
    2003
    166views Neural Networks» more  ESANN 2003»
    A recognition of filaments in solar images with an artificial neural network
    13 years 9 months ago
    A recognition of filaments in solar images with an artificial neural network
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    A new technique based on the Artificial Neural Network (ANN) was developed for an automated recognition of solar filaments, dark elongated features visible in the hydrogen H-alpha ...
    Valentina V. Zharkova, Vitaly Schetinin
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    ESANN
    1998
    142views Neural Networks» more  ESANN 1998»
    Lazy learning for control design
    13 years 9 months ago
    Lazy learning for control design
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    This paper presents two local methods for the control of discrete-time unknown nonlinear dynamical systems, when only a limited amount of input-output data is available. The modeli...
    Gianluca Bontempi, Mauro Birattari, Hugues Bersini
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    ESANN
    1998
    170views Neural Networks» more  ESANN 1998»
    Recurrent SOM with local linear models in time series prediction
    13 years 9 months ago
    Recurrent SOM with local linear models in time series prediction
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    Recurrent Self-Organizing Map (RSOM) is studied in three di erent time series prediction cases. RSOM is used to cluster the series into local data sets, for which corresponding lo...
    Timo Koskela, Markus Varsta, Jukka Heikkonen, Kimm...
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