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    ISNN
    2005
    Springer
    128views Neural Networks» more  ISNN 2005»
    A Learning Framework for Blind Source Separation Using Generalized Eigenvalues
    15 years 7 months ago
    A Learning Framework for Blind Source Separation Using Generalized Eigenvalues
    Download  www.comp.hkbu.edu.hk
    This paper presents a learning framework for blind source separation (BSS), in which the BSS is formulated as generalized Eigenvalue (GE) problem. Compared to the typical informati...
    Hailin Liu, Yiu-ming Cheung
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    ISNN
    2005
    Springer
    132views Neural Networks» more  ISNN 2005»
    Scaling the Kernel Function to Improve Performance of the Support Vector Machine
    15 years 7 months ago
    Scaling the Kernel Function to Improve Performance of the Support Vector Machine
    Download  www.dcs.warwick.ac.uk
    Abstract. The present study investigates a geometrical method for optimizing the kernel function of a support vector machine. The method is an improvement of the one proposed in [4...
    Peter Williams, Sheng Li, Jianfeng Feng, Si Wu
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    IWANN
    2005
    Springer
    147views Neural Networks» more  IWANN 2005»
    A Comparison of Evolutionary Approaches to the Shortest Common Supersequence Problem
    15 years 7 months ago
    A Comparison of Evolutionary Approaches to the Shortest Common Supersequence Problem
    Download  www.lcc.uma.es
    The Shortest Common Supersequence problem is a hard combinatorial optimization problem with numerous practical applications. Several evolutionary approaches are proposed for this p...
    Carlos Cotta
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    IWANN
    2005
    Springer
    140views Neural Networks» more  IWANN 2005»
    Direct and Recursive Prediction of Time Series Using Mutual Information Selection
    15 years 7 months ago
    Direct and Recursive Prediction of Time Series Using Mutual Information Selection
    Download  www.cis.hut.fi
    Abstract. This paper presents a comparison between direct and recursive prediction strategies. In order to perform the input selection, an approach based on mutual information is u...
    Yongnan Ji, Jin Hao, Nima Reyhani, Amaury Lendasse
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    TSD
    2005
    Springer
    96views Signal Processing» more  TSD 2005»
    Mapping the Speech Signal onto Electromagnetic Articulography Trajectories Using Support Vector Regression
    15 years 7 months ago
    Mapping the Speech Signal onto Electromagnetic Articulography Trajectories Using Support Vector Regression
    Download  users.uom.gr
    Abstract. We report work on the mapping between the speech signal and articulatory trajectories from the MOCHA database. Contrasting previous works that used Neural Networks for th...
    Asterios Toutios, Konstantinos G. Margaritis
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