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An Algorithm for Fuzzy Pattern Recognition Based on Neural Networks

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Book cover Intelligent Computing (ICIC 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4113))

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Abstract

According to principles of fuzzy mathematics and neural networks, a new model on neural networks, by which fuzzy patterns can be better recognized, is presented in this paper. This model combines the thoughts of neural networks and maximum membership function. Thus the insufficiency in semantic expressions of neural networks can be compensated for. In the meantime, more objective effect can be obtained than that by fuzzy pattern recognition method in fuzzy mathematics. Experimental results show that the method is valid in practical applications.

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References

  1. Xie, J., Liu, C.: Fuzzy Mathematic Method and Application. Huazhong University of Science and Technology Press, Wu Han (2000)

    Google Scholar 

  2. Pal, S.K., Mitra, S.: Neuro-Fuzzy Pattern Recognition Methods in Soft Computing. John Wiley, New York (1999)

    Google Scholar 

  3. Martin, H.T. (ed.): Neural Network Design. PWS Publishing Co., Boston (1997)

    Google Scholar 

  4. Stanley, L.E., Hsu-Shih, S., Shih, H.S.: Fuzzy and Multi-level Decision Making. An Interactive Computational Approach. Springer, London (2001)

    Google Scholar 

  5. Li, P.: A Weighted Fuzzy Reasoning Network and Its Application. Computer Engineering and Design 26(1), 188–190 (2005)

    Google Scholar 

  6. Xu, S.: Common Algorithm in Computer. Tsinghua University Press, Beijing (1995)

    Google Scholar 

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Author information

Authors and Affiliations

  1. School of information, Wuyi University, Jiangmen, Guangdong, 529020, P.R.C.

    Guohui He

  2. National Laboratory on Machine Perception, Peking University, Beijing, 100871

    Yinbo Qing

Authors
  1. Guohui He
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  2. Yinbo Qing
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Editor information

Editors and Affiliations

  1. Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, Anhui, China

    De-Shuang Huang

  2. Carnegie Mellon University,  

    Kang Li

  3. School of Electronics, Electrical Engineering and Computer Science, Queen’s University Belfast, Stranmillis Road, BT9 5AH, Belfast, UK

    George William Irwin

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© 2006 Springer-Verlag Berlin Heidelberg

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He, G., Qing, Y. (2006). An Algorithm for Fuzzy Pattern Recognition Based on Neural Networks. In: Huang, DS., Li, K., Irwin, G.W. (eds) Intelligent Computing. ICIC 2006. Lecture Notes in Computer Science, vol 4113. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11816157_33

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  • DOI: https://doi.org/10.1007/11816157_33

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-37271-4

  • Online ISBN: 978-3-540-37273-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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