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    ESANN
    2006
    108views Neural Networks» more  ESANN 2006»
    Rotation-based ensembles of RBF networks
    13 years 6 months ago
    Rotation-based ensembles of RBF networks
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    Abstract. Ensemble methods allow to improve the accuracy of classification methods. This work considers the application of one of these methods, named Rotation-based, when the clas...
    Juan José Rodríguez, Jesús Ma...
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    ESANN
    2006
    141views Neural Networks» more  ESANN 2006»
    Hierarchical analysis of GSM network performance data
    13 years 6 months ago
    Hierarchical analysis of GSM network performance data
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    In this study, a method for hierarchical examination and visualization of GSM data using the Self-Organizing Map (SOM) is described. The data is examined in few phases. At first te...
    Mikko Multanen, Kimmo Raivio, Pasi Lehtimäki
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    ESANN
    2006
    121views Neural Networks» more  ESANN 2006»
    Learning and discrimination through STDP in a top-down modulated associative memory
    13 years 6 months ago
    Learning and discrimination through STDP in a top-down modulated associative memory
    Download  www.dice.ucl.ac.be
    Abstract. This article underlines the learning and discrimination capabilities of a model of associative memory based on artificial networks of spiking neurons. Inspired from neuro...
    Anthony Mouraud, Hélène Paugam-Moisy
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    ESANN
    2006
    186views Neural Networks» more  ESANN 2006»
    Bayesian source separation: beyond PCA and ICA
    13 years 6 months ago
    Bayesian source separation: beyond PCA and ICA
    Download  www.dice.ucl.ac.be
    Blind source separation (BSS) has become one of the major signal and image processing area in many applications. Principal component analysis (PCA) and Independent component analys...
    Ali Mohammad-Djafari
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    ESANN
    2006
    114views Neural Networks» more  ESANN 2006»
    An algorithm for fast and reliable ESOM learning
    13 years 6 months ago
    An algorithm for fast and reliable ESOM learning
    Download  www.mybytes.de
    The training of Emergent Self-organizing Maps (ESOM ) with large datasets can be a computationally demanding task. Batch learning may be used to speed up training. It is demonstrat...
    Mario Nöcker, Fabian Mörchen, Alfred Ult...
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    ESANN
    2006
    97views Neural Networks» more  ESANN 2006»
    Generalization properties of spiking neurons trained with ReSuMe method
    13 years 6 months ago
    Generalization properties of spiking neurons trained with ReSuMe method
    Download  www.dice.ucl.ac.be
    In this paper we demonstrate the generalization property of spiking neurons trained with ReSuMe method. We show in a set of experiments that the learning neuron can approximate the...
    Filip Ponulak, Andrzej J. Kasinski
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    ESANN
    2006
    130views Neural Networks» more  ESANN 2006»
    Cluster detection algorithm in neural networks
    13 years 6 months ago
    Cluster detection algorithm in neural networks
    Download  liris.cnrs.fr
    Complex networks have received much attention in the last few years, and reveal global properties of interacting systems in domains like biology, social sciences and technology. O...
    David Meunier, Hélène Paugam-Moisy
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    ESANN
    2006
    599views Neural Networks» more  ESANN 2006»
    Learning Visual Invariance
    13 years 6 months ago
    Learning Visual Invariance
    Download  www.dice.ucl.ac.be
    Invariance is a necessary feature of a visual system able to recognize real objects in all their possible appearance. It is also the processing step most problematic to understand ...
    Alessio Plebe
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    ESANN
    2006
    236views Neural Networks» more  ESANN 2006»
    Using Regression Error Characteristic Curves for Model Selection in Ensembles of Neural Networks
    13 years 6 months ago
    Using Regression Error Characteristic Curves for Model Selection in Ensembles of Neural Networks
    Download  www.dice.ucl.ac.be
    Regression Error Characteristic (REC) analysis is a technique for evaluation and comparison of regression models that facilitates the visualization of the performance of many regre...
    Aloísio Carlos de Pina, Gerson Zaverucha
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    ESANN
    2006
    170views Neural Networks» more  ESANN 2006»
    Discriminacy of the minimum range approach to blind separation of bounded sources
    13 years 6 months ago
    Discriminacy of the minimum range approach to blind separation of bounded sources
    Download  ljk.imag.fr
    The Blind Source Separation (BSS) problem is often solved by maximizing objective functions reflecting the statistical dependency between outputs. Since global maximization may be ...
    Dinh-Tuan Pham, Frédéric Vrins
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