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Boolean Factor Analysis by Expectation-Maximization Method

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F13%3A00368469" target="_blank" >RIV/67985807:_____/13:00368469 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Boolean Factor Analysis by Expectation-Maximization Method

  • Original language description

    Boolean factor analysis is one of the most efficient methods to reveal and to overcome informational redundancy of high-dimensional binary signals. In the present study, we introduce new Expectation-Maximization method which maximizes the likelihood of Boolean factor analysis solution. Using the so-called bars problem benchmark, we compare efficiencies of the proposed method with Dendritic Inhibition neural network.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    BB - Applied statistics, operational research

  • OECD FORD branch

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    Z - Vyzkumny zamer (s odkazem do CEZ)

Others

  • Publication year

    2013

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings of the Third International Conference on Intelligent Human Computer Interaction IHCI 2011

  • ISBN

    978-3-642-31602-9

  • ISSN

  • e-ISSN

  • Number of pages

    12

  • Pages from-to

    243-254

  • Publisher name

    Springer

  • Place of publication

    Heidelberg

  • Event location

    Prague

  • Event date

    Aug 29, 2011

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000312116400021