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On Non-markovian Topographic Organization of Receptive Fields in Recursive Self-organizing Map

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Advances in Natural Computation (ICNC 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3611))

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Abstract

Recently, there has been an outburst of interest in extending topographic maps of vectorial data to more general data structures, such as sequences or trees. The representational capabilities and internal representations of the models are not well understood. We concentrate on a generalization of the Self-Organizing Map (SOM) for processing sequential data – the Recursive SOM (RecSOM [1]). We argue that contractive fixed-input dynamics of RecSOM is likely to lead to Markovian organizations of receptive fields on the map. We show that Markovian topographic maps of sequential data can be produced using a simple fixed (non-adaptable) dynamic module externally feeding a standard topographic model designed to process static vectorial data of fixed dimensionality (e.g. SOM). We elaborate upon the importance of non-Markovian organizations in topographic maps of sequential data.

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© 2005 Springer-Verlag Berlin Heidelberg

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Tiňo, P., Farkaš, I. (2005). On Non-markovian Topographic Organization of Receptive Fields in Recursive Self-organizing Map. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539117_96

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  • DOI: https://doi.org/10.1007/11539117_96

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28325-6

  • Online ISBN: 978-3-540-31858-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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