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Temporal Hebbian Self-Organizing Map for Sequences

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F08%3A00145486" target="_blank" >RIV/68407700:21230/08:00145486 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Temporal Hebbian Self-Organizing Map for Sequences

  • Original language description

    In this paper we present a new self-organizing neural network called Temporal Hebbian Self-organizing Map (THSOM) suitable for modelling of temporal sequences. The network is based on Kohonen's Self-organizing Map, which is extended with a layer of fullrecurrent connections among the neurons. The layer of recurrent connections is trained with Hebb's rule. The recurrent layer represents temporal order of the input vectors. The THSOM brings a straightforward way of embedding context information in recurrent SOM using neurons with Euclidean metric and scalar product. The recurrent layer can be easily converted into a stochastic automaton (Markov Chain) generating sequences used for previous THSOM training. Finally, two real world examples of THSOM usageare presented. THSOM was applied to extraction of road network from GPS data and to construction of spatio-temporal models of spike train sequences measured in human brain in vivo.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    Z - Vyzkumny zamer (s odkazem do CEZ)

Others

  • Publication year

    2008

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Artificial Neural Networks - ICANN 2008, PT I

  • ISBN

    978-3-540-87535-2

  • ISSN

    0302-9743

  • e-ISSN

  • Number of pages

    10

  • Pages from-to

  • Publisher name

    Springer

  • Place of publication

    Heidelberg

  • Event location

    Prague

  • Event date

    Sep 3, 2008

  • Type of event by nationality

    EUR - Evropská akce

  • UT code for WoS article

    000259566200065