Recursive self-organizing map as a contractive iterative function system

Peter Tiňo, Igor Farkaš, Jort van Mourik

    Research output: Chapter in Book/Published conference outputChapter


    Recently, there has been a considerable research activity in extending topographic maps of vectorial data to more general data structures, such as sequences or trees. However, the representational capabilities and internal representations of the models are not well understood. We rigorously analyze a generalization of the Self-Organizing Map (SOM) for processing sequential data, Recursive SOM (RecSOM [1]), as a non-autonomous dynamical system consisting off a set of fixed input maps. We show that contractive fixed input maps are likely to produce Markovian organizations of receptive fields o the RecSOM map. We derive bounds on parameter $\beta$ (weighting the importance of importing past information when processing sequences) under which contractiveness of the fixed input maps is guaranteed.
    Original languageEnglish
    Title of host publicationIntelligent Data Engineering and Automated Learning - IDEAL 2005
    EditorsMarcus Gallagher, James Hogan, Frederic Maire
    Place of PublicationBerlin (DE)
    Number of pages8
    ISBN (Print)978-3-540-26972-4
    Publication statusPublished - 20 Jun 2005

    Publication series

    NameLecture Notes in Computer Science


    • topographic maps
    • vectorial data
    • contractive fixed input map
    • Markovian organization
    • receptive fields
    • RecSOM map


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