• DocumentCode
    1713829
  • Title

    Neural Network Rule Extraction and the LED Display Recognition Problem

  • Author

    Setiono, Rudy ; Tanaka, Masahiro

  • Author_Institution
    Sch. of Comput., Nat. Univ. of Singapore, Singapore, Singapore
  • Volume
    2
  • fYear
    2010
  • Firstpage
    53
  • Lastpage
    56
  • Abstract
    This paper presents the results from a neural network rule extraction algorithm applied to the LED display recognition problem. We show that pruned neural networks with small number of hidden nodes and connections are able to recognize all the 10 digits from 0 to 9. Earlier work by other researchers demonstrated how symbolic fuzzy rules can be extracted from trained neural networks to solve this problem. Our rules in contrast are crisp rules, and they are obtained from smaller networks. As a result, simpler and easier to understand rules are obtained. These rules give us an insight of how neural networks differentiate one digit from the rest in LED display recognition problem.
  • Keywords
    LED displays; fuzzy neural nets; LED display recognition; neural network rule extraction; symbolic fuzzy rules; Accuracy; Artificial neural networks; Data mining; Light emitting diodes; Machine learning algorithms; Noise; Training; LED display recognition; pruning; rule extraction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Tools with Artificial Intelligence (ICTAI), 2010 22nd IEEE International Conference on
  • Conference_Location
    Arras
  • ISSN
    1082-3409
  • Print_ISBN
    978-1-4244-8817-9
  • Type

    conf

  • DOI
    10.1109/ICTAI.2010.83
  • Filename
    5671432