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An Enhanced Fuzzy Multilayer Perceptron

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Neural Information Processing (ICONIP 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3316))

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Abstract

Error back-propagation algorithm of the multilayer perceptron may result in local-minima because of the insufficient nodes in the hidden layer, inadequate momentum set-up, and initial weights. In this paper, we proposed the fuzzy multilayer perceptron which is composed of the ART1 and the fuzzy neural network. The proposed fuzzy multilayer perceptron using the self-generation method applies not only the ART1 to create the nodes from the input layer to the hidden layer, but also the winner-take-all method, modifying stored patterns according to specific patterns, to adjustment of weights. The proposed learning method was applied to recognize individual numbers of student identification cards. Our experimental result showed that the possibility of local-minima was decreased and the learning speed and the paralysis were improved more than the conventional error back-propagation algorithm.

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Author information

Authors and Affiliations

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

    Kwang Baek Kim

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

    Choong Shik Park

Authors
  1. Kwang Baek Kim
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  2. Choong Shik Park
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Editor information

Editors and Affiliations

  1. Indian Statistical Institute, Electronics and Communication Sciences Unit, Kolkata, India

    Nikhil Ranjan Pal

  2. School of Computer and Information Sciences, Knowledge Engineering and Discovery Research Institute (KEDRI), Auckland University of Technology, Private Bag 92006, Auckland, New Zealand

    Nik Kasabov

  3. Department of Instrumentation and Electronics Engineering, Jadavpur University, Salt-lake Campus, 700098, Calcutta, India

    Rajani K. Mudi

  4. Indian Statistical Institute, 203 B. T. Road, 700 108, Calcutta,  

    Srimanta Pal

  5. Indian Statistical Institute, Computer Vision and Pattern Recognition Unit, 700108, Kolkata, India

    Swapan Kumar Parui

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© 2004 Springer-Verlag Berlin Heidelberg

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Kim, K.B., Park, C.S. (2004). An Enhanced Fuzzy Multilayer Perceptron. In: Pal, N.R., Kasabov, N., Mudi, R.K., Pal, S., Parui, S.K. (eds) Neural Information Processing. ICONIP 2004. Lecture Notes in Computer Science, vol 3316. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30499-9_151

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  • DOI: https://doi.org/10.1007/978-3-540-30499-9_151

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23931-4

  • Online ISBN: 978-3-540-30499-9

  • eBook Packages: Springer Book Archive

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