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The Learning Algorithm for a Novel Fuzzy Neural Network

  • Conference paper
Book cover Intelligent Computing (ICIC 2006)

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

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Abstract

Symmetric polygonal fuzzy numbers are employed to construct a class of novel feedforward fuzzy neural networks (FNN’s)—the polygonal FNN’s. Their input–output (I/O) relationships are built upon a novel fuzzy arithmetic and extension principle for the polygonal fuzzy numbers. We build the topological architecture of a three layer polygonal FNN, and present its I/O relationship representation. Also the fuzzy BP learning algorithm for the polygonal fuzzy number connection weights and thresholds is developed based on calculus of max–min (∨– ∧) functions. At last some simulation examples are compared to show that our model possess strong I/O ability and generalization capability.

This work was supported by grants from the National Natural Sciences Foundation of China (No.60375023 and No. 60574059) and the National Basic Research Program of China (No. 2005CB321800).

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Author information

Authors and Affiliations

  1. Department of Mathematics, National University of Defense Technology, Changsha, Hunan, 410073, P.R. China

    Puyin Liu, Qiang Luo, Wenqiang Yang & Dongyun Yi

Authors
  1. Puyin Liu
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  2. Qiang Luo
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  3. Wenqiang Yang
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  4. Dongyun Yi
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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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Liu, P., Luo, Q., Yang, W., Yi, D. (2006). The Learning Algorithm for a Novel Fuzzy Neural Network. 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_24

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  • DOI: https://doi.org/10.1007/11816157_24

  • 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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