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    ESANN
    2006
    116views Neural Networks» more  ESANN 2006»
    Outlier identification with the Harmonic Topographic Mapping
    14 years 28 days ago
    Outlier identification with the Harmonic Topographic Mapping
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    We review two versions of a topology preserving algorithm one of which we had previously [1] found to be more successful in defining smooth manifolds and tight clusters. In the con...
    Marian Pena, Colin Fyfe
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    ESANN
    2006
    105views Neural Networks» more  ESANN 2006»
    A simple idea to separate convolutive mixtures in an undetermined scenario
    14 years 28 days ago
    A simple idea to separate convolutive mixtures in an undetermined scenario
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    We consider a blind separation problem for undetermined mixtures of two BPSK signals in a multi-path fading channel. We use independence and frequency diversity of the two source s...
    Maciej Pedzisz, Ali Mansour
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    ESANN
    2006
    94views Neural Networks» more  ESANN 2006»
    On-line adaptation of neuro-prostheses with neuronal evaluation signals
    14 years 28 days ago
    On-line adaptation of neuro-prostheses with neuronal evaluation signals
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    Klaus Pawelzik, Udo A. Ernst, David Rotermund
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    ESANN
    2006
    157views Neural Networks» more  ESANN 2006»
    Data mining techniques for feature selection in blood cell recognition
    14 years 28 days ago
    Data mining techniques for feature selection in blood cell recognition
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    The paper presents and compares the data mining techniques for selection of the diagnostic features in the problem of blood cell recognition in leukemia. Different techniques are c...
    Tomasz Markiewicz, Stanislaw Osowski
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    ESANN
    2006
    105views Neural Networks» more  ESANN 2006»
    Evolving multi-segment 'super-lamprey' CPG's for increased swimming control
    14 years 28 days ago
    Evolving multi-segment 'super-lamprey' CPG's for increased swimming control
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    Abstract. `Super-lamprey' swimmers which operate over a greater control range are evolved. Propulsion in the lamprey, an eel-like fish, is governed by activity in its spinal n...
    Leena N. Patel, Alan F. Murray, John Hallam
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    ESANN
    2006
    119views Neural Networks» more  ESANN 2006»
    Probabilistic classifiers and time-scale representations: application to the monitoring of a tramway guiding system
    14 years 28 days ago
    Probabilistic classifiers and time-scale representations: application to the monitoring of a tramway guiding system
    Download  www.isima.fr
    Zahra Hamou Mamar, Pierre Chainais, Alexandre Auss...
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    ESANN
    2006
    158views Neural Networks» more  ESANN 2006»
    Dynamical reservoir properties as network effects
    14 years 28 days ago
    Dynamical reservoir properties as network effects
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    It has been proposed that chaos can serve as a reservoir providing an infinite number of dynamical states [1, 2, 3, 4, 5]. These can be interpreted as different behaviors, search a...
    Carlos Lourenço
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    ESANN
    2006
    119views Neural Networks» more  ESANN 2006»
    EM-algorithm for training of state-space models with application to time series prediction
    14 years 28 days ago
    EM-algorithm for training of state-space models with application to time series prediction
    Download  eprints.pascal-network.org
    In this paper, an improvement to the E step of the EM algorithm for nonlinear state-space models is presented. We also propose strategies for model structure selection when the EM-...
    Elia Liitiäinen, Nima Reyhani, Amaury Lendass...
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    ESANN
    2006
    96views Neural Networks» more  ESANN 2006»
    Selection of more than one gene at a time for cancer prediction from gene expression data
    14 years 28 days ago
    Selection of more than one gene at a time for cancer prediction from gene expression data
    Download  www.dice.ucl.ac.be
    A new gene selection method capable of selecting more than one gene at a time is introduced. This characteristic contrasts it with almost all known methods assuming that there are ...
    Oleg Okun, Nikolay G. Zagoruiko, Alexessander Alve...
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    ESANN
    2006
    164views Neural Networks» more  ESANN 2006»
    A Gaussian process latent variable model formulation of canonical correlation analysis
    14 years 28 days ago
    A Gaussian process latent variable model formulation of canonical correlation analysis
    Download  www.dice.ucl.ac.be
    Abstract. We investigate a nonparametric model with which to visualize the relationship between two datasets. We base our model on Gaussian Process Latent Variable Models (GPLVM)[1...
    Gayle Leen, Colin Fyfe
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