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Enhanced Fuzzy Single Layer Learning Algorithm Using Automatic Tuning of Threshold

  • Conference paper
Computational Science and Its Applications - ICCSA 2006 (ICCSA 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3982))

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Abstract

In this paper, we proposed an enhanced fuzzy single layer learning algorithm using the dynamic adjustment of threshold. For performance evaluation, the proposed method was applied to the XOR problem, which is used as a benchmark in the field of pattern recognition, and the recognition of digital image in a practical image processing application. As a result of experiment, though the method does not always guarantee the convergence, it shows the improved learning time and the high convergence rate.

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© 2006 Springer-Verlag Berlin Heidelberg

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Kim, KB., Lee, BK., Kim, SH. (2006). Enhanced Fuzzy Single Layer Learning Algorithm Using Automatic Tuning of Threshold. In: Gavrilova, M., et al. Computational Science and Its Applications - ICCSA 2006. ICCSA 2006. Lecture Notes in Computer Science, vol 3982. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11751595_19

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  • DOI: https://doi.org/10.1007/11751595_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34075-1

  • Online ISBN: 978-3-540-34076-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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