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Bulevskij faktornyj analiz na osnove attraktornoj nejronnoj seti i nekotoryje ego priloženija

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    SYSNO ASEP0360031
    Document TypeJ - Journal Article
    R&D Document TypeJournal Article
    Subsidiary JOstatní články
    TitleBulevskij faktornyj analiz na osnove attraktornoj nejronnoj seti i nekotoryje ego priloženija
    TitleBulev factorial analysis by means of attractor neural network and its some appendices
    Author(s) Frolov, A. A. (RU)
    Húsek, Dušan (UIVT-O) RID, SAI, ORCID
    Polyakov, P.Y. (RU)
    Source TitleNejrokomp'jutery: razrabotka, primenenie - ISSN 1999-8554
    -, č. 1 (2011), s. 25-46
    Number of pages22 s.
    Languagerus - Russian
    CountryRU - Russian Federation
    KeywordsBoolean factor analysis ; recurrent neural network ; Hopfield-like neural network ; associative memory ; unsupervised learning
    Subject RIVIN - Informatics, Computer Science
    R&D ProjectsGAP202/10/0262 GA ČR - Czech Science Foundation (CSF)
    GA205/09/1079 GA ČR - Czech Science Foundation (CSF)
    CEZAV0Z10300504 - UIVT-O (2005-2011)
    AnnotationObyčnoj zadačej, vstrečajuščejsa pri analize bolšich objemov dannych, javlaetsa poisk ich adekvatnogo predstavlenija v prostranstve menšej razmernosti. Odnim iz naiboleje effektivnych ispolzujemych dla etogo metodov javljaetsa faktornyj analiz. V nastojaščej rabote my predlagaem ispolzovať v kačestve metoda bulevskogo faktornogo analiza attraktornuju nejronnuju seť tipa Chopfilda. Osobennosti funkcionirovania predlagaemoj nejronnoj seti objasnajutsa šag za šagom na primere bulevskogo faktornogo analiza iskusstvenno sozdannogo massiva dannych. V zaključenie my demonstrirujem effektivnosť metoda v priloženii k analizu rezultatov golosovanija v Gosudarstvennoj dume RF i analizu statej, predstavlennych na Meždunarodnoj konferencii po nejronnym seťam.
    Description in EnglishThe usual problem meeting at the analysis of great volumes of data, search of their adequate representation in space of smaller dimension is. One of the most effective methods used for it is the factorial analysis. In the present work we suppose to use as a method Bulean the factorial analysis attractor of the Hopfield neural network. Features of functioning of an offered neural network speak step by step an example Bulean the factorial analysis is artificial the created data file. Efficiency of a method in the appendix to the analysis of results of voting in the State Dumas of the Russian Federation and is shown to the analysis of clauses presented on the International conferences on neural networks.
    WorkplaceInstitute of Computer Science
    ContactTereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800
    Year of Publishing2012
    Electronic addresshttp://www.radiotec.ru/catalog.php?cat=jr7&art=8576
Number of the records: 1  

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