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Pattern Recognition Based on Similarity in Linear Semi-ordered Spaces

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Hybrid Artificial Intelligent Systems (HAIS 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6678))

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Abstract

In the paper an approach to pattern recognition based on a notion of similarity in linear semi-ordered (Kantorovitsch) space is presented. It is compared with other approaches based on the metric distance and on angular dilation measures in observation spaces. Basic assumptions of the Kantorovitsch space are shortly presented. It is shown that finite reference sets for pattern recognition take on in Kantorovitsch space formal structures presented by connectivity graphs which facilitate finding the reference vectors for pattern recognition.

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Author information

Authors and Affiliations

  1. M. Nalecz Institute of Biocybernetics and Biomedical Engineering PAS, 4 Ks. Trojdena Str., 02-109, Warsaw, Poland

    Juliusz L. Kulikowski & Malgorzata Przytulska

Authors
  1. Juliusz L. Kulikowski
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  2. Malgorzata Przytulska
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Editor information

Editors and Affiliations

  1. GICAP Research Group, University of Burgos, 09006, Burgos, Spain

    Emilio Corchado

  2. Wroclaw University of Technology, 50-370, Wroclaw, Poland

    Marek Kurzyński  & Michał Woźniak  & 

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© 2011 Springer-Verlag Berlin Heidelberg

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Kulikowski, J.L., Przytulska, M. (2011). Pattern Recognition Based on Similarity in Linear Semi-ordered Spaces. In: Corchado, E., Kurzyński, M., Woźniak, M. (eds) Hybrid Artificial Intelligent Systems. HAIS 2011. Lecture Notes in Computer Science(), vol 6678. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21219-2_3

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  • DOI: https://doi.org/10.1007/978-3-642-21219-2_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21218-5

  • Online ISBN: 978-3-642-21219-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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