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    COMPLIFE
    2006
    Springer
    243views Applied Computing» more  COMPLIFE 2006»
    Set-Oriented Dimension Reduction: Localizing Principal Component Analysis Via Hidden Markov Models
    13 years 8 months ago
    Set-Oriented Dimension Reduction: Localizing Principal Component Analysis Via Hidden Markov Models
    Download  biocomputing.mi.fu-berlin.de
    We present a method for simultaneous dimension reduction and metastability analysis of high dimensional time series. The approach is based on the combination of hidden Markov model...
    Illia Horenko, Johannes Schmidt-Ehrenberg, Christo...
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