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An Enhanced Fuzzy Neural Network

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Parallel and Distributed Computing: Applications and Technologies (PDCAT 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3320))

Abstract

In this paper, we propose a novel approach for evolving the architecture of a multi-layer neural network. Our method uses combined ART1 algorithm and Max-Min neural network to self-generate nodes in the hidden layer. We have applied the proposed method to the problem of recognizing ID number in identity cards. Experimental results with a real database show that the proposed method has better performance than a conventional neural network.

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References

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Author information

Authors and Affiliations

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

    Kwang Baek Kim

  2. School of Electronic and Information Engneering, Kunsan National University, S. Korea

    Young-Hoon Joo

  3. Dept. of Computer Information, Catholic University of Pusan, S. Korea

    Jae-Hyun Cho

Authors
  1. Kwang Baek Kim
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  2. Young-Hoon Joo
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  3. Jae-Hyun Cho
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Editor information

Editors and Affiliations

  1. Nanyang Centre for Supercomputing and Visualisation School of Mechanical and Production Engineering, Nanyang Technological University, 50 Nanyang Avenue, 639 798, Singapore

    Kim-Meow Liew

  2. School of Computer Science, The University of Adelaide,  

    Hong Shen

  3. Asia Pacific Science and Technology Center, Sun Microsystems Inc., 50 Nanyang Avenue, N3-1c-10, 639798, Singapore

    Simon See

  4. School of Computer Engineering, Nanyang Technological University, 639798, Singapore

    Wentong Cai

  5. Southwest Jiaotong University,  

    Pingzhi Fan

  6. Tohoku University ,  

    Susumu Horiguchi

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© 2004 Springer-Verlag Berlin Heidelberg

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Kim, K.B., Joo, YH., Cho, JH. (2004). An Enhanced Fuzzy Neural Network. In: Liew, KM., Shen, H., See, S., Cai, W., Fan, P., Horiguchi, S. (eds) Parallel and Distributed Computing: Applications and Technologies. PDCAT 2004. Lecture Notes in Computer Science, vol 3320. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30501-9_40

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  • DOI: https://doi.org/10.1007/978-3-540-30501-9_40

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-24013-6

  • Online ISBN: 978-3-540-30501-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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