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Feature Detection by Structural Enhanced Information

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Advances in Neuro-Information Processing (ICONIP 2008)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5507))

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Abstract

In this paper, we propose structural enhanced information for detecting main features in input patterns. In structural enhanced information, three types of enhanced information can be differentiated, that is, the first-, the second- and the third-order enhanced information. The first-order information is related to the enhancement of competitive units themselves through some elements in a network, and the second-order information is dependent upon the enhancement of competitive units with input patterns. Then, the third-order information is obtained by subtracting the effect of the first-order information from the second-order information. Thus, the third-order information more explicitly represents information on input patterns. With this structural enhanced information, we can estimate more detailed features in input patterns. We applied the method to the well-known Iris problem. In both problems, we succeeded in extracting detailed and important features especially by using the third-order information.

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Author information

Authors and Affiliations

  1. IT Education Center, Tokai University, 1117 Kitakaname Hiratsuka, Kanagawa, 259-1292, Japan

    Ryotaro Kamimura

Authors
  1. Ryotaro Kamimura
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Editor information

Editors and Affiliations

  1. Network Design and Research Center, Kyushu Institute of Technology,, 680-4, Kawazu, Iizuka,, 820-8502, Fukuoka, Japan

    Mario Köppen

  2. Knowledge Engineering and Discovery Research Institute (KEDRI), School of Computing and Mathematical Sciences, Auckland University of Technology, 350 Queen Street, 10110, Auckland, New Zealand

    Nikola Kasabov

  3. Department of Electrical and Computer Engineering, Robotics Laboratory, Auckland University of Technology, 38 Princes Street,, 1142, Auckland, New Zealand

    George Coghill

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© 2009 Springer-Verlag Berlin Heidelberg

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Kamimura, R. (2009). Feature Detection by Structural Enhanced Information. In: Köppen, M., Kasabov, N., Coghill, G. (eds) Advances in Neuro-Information Processing. ICONIP 2008. Lecture Notes in Computer Science, vol 5507. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03040-6_21

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  • DOI: https://doi.org/10.1007/978-3-642-03040-6_21

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03039-0

  • Online ISBN: 978-3-642-03040-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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