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Enhanced Fuzzy Single Layer Learning Algorithm Using Automatic Tuning of Threshold

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Book cover 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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References

  1. Judith, E.D.: Neural Network Architectures An Introduction. Van Nostrand Reinhold, New York (1990)

    Google Scholar 

  2. Gupta, M.M., Qi, J.: On Fuzzy Neuron Models. Proceedings of IJCNN 2, 431–435 (1991)

    MathSciNet  Google Scholar 

  3. Goh, T.H., Wang, P.Z., Lui, H.C.: Learning Algorithm for Enhanced Fuzzy Perceptron. Proceedings of IJCNN 2, 435–440 (1992)

    Google Scholar 

  4. Kim, K.B., Cha, E.Y.: A New Single Layer Perceptron using Fuzzy Neural Controller. In: Jaime, O., Ariel, S. (eds.) Simulators International XII, vol. 27(3), pp. 341–343 (1995)

    Google Scholar 

  5. Kim, K.B., Kim, S., Joo, Y., Oh, A.S.: Enhanced Fuzzy Single Layer Perceptron. In: Wang, J., Liao, X.-F., Yi, Z. (eds.) ISNN 2005. LNCS, vol. 3496, pp. 603–608. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  6. Kim, K.B., Seo, C.J., Yang, H.K.: A Biological Fuzzy Multilayer Perceptron Algorithm. Journal of KIMICS 1(1), 99–103 (2003)

    Google Scholar 

  7. Kim, T.K., Yun, H.G., Lho, Y.W., Kim, K.B.: An Educational Matters Administration System on the Web by Using Image Recognition. In: Proceedings of Korea Intelligent Information Systems, pp. 203–209 (2002)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Dept. of Computer Engineering, Silla University, Korea

    Kwang-Baek Kim

  2. Dept. of Computer Engineering, Kwandong University, Korea

    Byung-Kwan Lee

  3. Dept. of Automotive Mechanical Engineering, Silla University, Korea

    Soon-Ho Kim

Authors
  1. Kwang-Baek Kim
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  2. Byung-Kwan Lee
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  3. Soon-Ho Kim
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Calgary, 2500 University Drive N.W., T2N 1N4, Calgary, AB, Canada

    Marina Gavrilova

  2. Department of Mathematics and Computer Science, University of Perugia, via Vanvitelli, 1, I-06123, Perugia, Italy

    Osvaldo Gervasi

  3. William Norris Professor, Head of the Computer Science and Engineering Department, University of Minnesota, USA

    Vipin Kumar

  4. OptimaNumerics Ltd., Cathedral House, 23-31 Waring Street, BT1 2DX, Belfast, UK

    C. J. Kenneth Tan

  5. Clayton School of IT, Monash University, 3800, Clayton, Australia

    David Taniar

  6. Department of Chemistry, University of Perugia, Via Elce di Sotto, 8, I-06123, Perugia, Italy

    Antonio Laganá

  7. School of Computing, Soongsil University, Seoul, Korea

    Youngsong Mun

  8. School of Information and Communication Engineering, Sungkyunkwan University, Korea

    Hyunseung Choo

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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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