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    Faculty of Informatics, Eotvos Lorand University

    Independent Process Analysis without A Priori Dimensional Information

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    Recently, several algorithms have been proposed for independent subspace analysis where hidden variables are i.i.d. processes. We show that these methods can be extended to certain AR, MA, ARMA and ARIMA tasks. Central to our paper is that we introduce a cascade of algorithms, which aims to solve these tasks without previous knowledge about the number and the dimensions of the hidden processes. Our claim is supported by numerical simulations. As a particular application, we search for subspaces of facial components.

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    Description

    Title : Independent Process Analysis without A Priori Dimensional Information
    Author(s) : Barnabas Poczos, Zoltan Szabo, Melinda Kiszlinger, Andras Lorincz
    Abstract : Recently, several algorithms have been proposed for independent subspace analysis where hidden variables are i.i.d. processes. We show that these methods can be extended to certain AR, MA, ARMA and ARIMA tasks. Central to our paper is that we introduce a cascade of algorithms, which aims to solve these tasks without previous knowledge about the number and the dimensions of the hidden processes. Our claim is supported by numerical simulations. As a particular application, we search for subspaces of facial components.
    Subject : unspecified
    Area : Other
    Language : English
    Year : 2007

    Affiliations Faculty of Informatics, Eotvos Lorand University
    Journal : Analysis
    Issue : i
    Pages : 9
    Url : http://arxiv.org/abs/math/0703612

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