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    IJON
    2006
    91views more  IJON 2006»
    Symmetry axis extraction by a neural network
    13 years 11 months ago
    Symmetry axis extraction by a neural network
    Download  www.cs.stir.ac.uk
    This paper proposes a neural network model that extracts axes of symmetry from visual patterns. The input patterns can be line drawings, plane figures or gray-scaled natural image...
    Kunihiko Fukushima, Masayuki Kikuchi
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    IJON
    2006
    64views more  IJON 2006»
    Extraction of temporally correlated sources with its application to non-invasive fetal electrocardiogram extraction
    13 years 11 months ago
    Extraction of temporally correlated sources with its application to non-invasive fetal electrocardiogram extraction
    Download  dsp.ucsd.edu
    This letter addresses the problem of fetal electrocardiogram (FECG) extraction. A class of source extraction algorithms is proposed, which uses a combination of two different appr...
    Zhi-Lin Zhang, Zhang Yi
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    IJON
    2006
    77views more  IJON 2006»
    Robust extraction of specific signals with temporal structure
    13 years 11 months ago
    Robust extraction of specific signals with temporal structure
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    There is a trend to develop blind or semi-blind source extraction algorithms based on second-order statistics, due to its low computation load and fast processing speed. An import...
    Zhi-Lin Zhang, Zhang Yi
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    IJON
    2006
    169views more  IJON 2006»
    Denoising using local projective subspace methods
    13 years 11 months ago
    Denoising using local projective subspace methods
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    In this paper we present denoising algorithms for enhancing noisy signals based on Local ICA (LICA), Delayed AMUSE (dAMUSE) and Kernel PCA (KPCA). The algorithm LICA relies on app...
    Peter Gruber, Kurt Stadlthanner, Matthias Böh...
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    IJON
    2006
    111views more  IJON 2006»
    Dynamic pruning algorithm for multilayer perceptron based neural control systems
    13 years 11 months ago
    Dynamic pruning algorithm for multilayer perceptron based neural control systems
    Download  www.jhuapl.edu
    Generalization ability of neural networks is very important and a rule of thumb for good generalization in neural systems is that the smallest system should be used to fit the tra...
    Jie Ni, Qing Song
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    IJON
    2006
    74views more  IJON 2006»
    Spatio-temporal information coding in the cuneate nucleus
    13 years 11 months ago
    Spatio-temporal information coding in the cuneate nucleus
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    The dorsal column nuclei, cuneatus and gracilis, receive somesthetic information impinging on projection cells and local inhibitory interneurons. The presence of these interneuron...
    Juan Navarro, Eduardo Sánchez, Antonio Cane...
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    IJON
    2006
    84views more  IJON 2006»
    Cycle-to-cycle variability as an optimal behavioral strategy
    13 years 11 months ago
    Cycle-to-cycle variability as an optimal behavioral strategy
    Download  transmitter.neuro.mssm.edu
    Aplysia feeding behavior is highly variable from cycle to cycle. In some cycles, when the variability causes a mismatch between the animal's movements and the requirements of...
    Vladimir Brezina, Alex Proekt, Klaudiusz R. Weiss
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    IJON
    2006
    109views more  IJON 2006»
    Associative memory of connectivity patterns
    13 years 11 months ago
    Associative memory of connectivity patterns
    Download  fias.uni-frankfurt.de
    The goal of the visual correspondence problem is to establish a connectivity pattern (a mapping) between two images such that features projected from the same scene point are conn...
    Junmei Zhu, Christoph von der Malsburg
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    IJON
    2006
    40views more  IJON 2006»
    A new biclustering technique based on crossing minimization
    13 years 11 months ago
    A new biclustering technique based on crossing minimization
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    Ahsan Abdullah, Amir Hussain
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    IJON
    2006
    82views more  IJON 2006»
    Modeling single neuron behavior using stochastic differential equations
    13 years 11 months ago
    Modeling single neuron behavior using stochastic differential equations
    Download  sp.cs.tut.fi
    We model the intrinsic dynamic behavior of a neuron using stochastic differential equations and Brownian motion. Basis of our work is the deterministic one-compartmental multi-con...
    Antti Saarinen, Marja-Leena Linne, Olli Yli-Harja
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