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    ESANN
    2000
    87views Neural Networks» more  ESANN 2000»
    A comparative design of a MIMO neural adaptive rate damping for a nonlinear helicopter model
    13 years 8 months ago
    A comparative design of a MIMO neural adaptive rate damping for a nonlinear helicopter model
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    Using a nonlinear 15-state helicopter model in 6 DOF, two di erent neural control systems, both acting as rate damping, have been designed and compared. They are both based on the ...
    Piero A. Gili, Manuela Battipede
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    ESANN
    2000
    125views Neural Networks» more  ESANN 2000»
    A neural network approach to adaptive pattern analysis - the deformable feature map
    13 years 8 months ago
    A neural network approach to adaptive pattern analysis - the deformable feature map
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    Abstract. In this paper, we presen t an algorithm that provides adaptive plasticity in function approximation problems: the deformable (feature) map (DM) algorithm. The DM approach...
    Axel Wismüller, Frank Vietze, Dominik R. Ders...
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    ESANN
    2003
    111views Neural Networks» more  ESANN 2003»
    On the weight dynamics of recurrent learning
    13 years 8 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
    2000
    95views Neural Networks» more  ESANN 2000»
    The K.U.Leuven competition data: a challenge for advanced neural network techniques
    13 years 8 months ago
    The K.U.Leuven competition data: a challenge for advanced neural network techniques
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    In this paper we shortly discuss the K.U. Leuven time-series prediction competition, which has been held in the framework of the International Workshop on Advanced Black-Box Techni...
    Johan A. K. Suykens, Joos Vandewalle
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    ESANN
    2000
    139views Neural Networks» more  ESANN 2000»
    Evaluating SOMs using order metrics
    13 years 8 months ago
    Evaluating SOMs using order metrics
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    It has been shown that self-organized maps, when adequately trained with the set of integers 1 to 32, lay out real numbers in a 2D map in an ordering that is superior to any of the...
    Arnulfo P. Azcarraga
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