• DocumentCode
    1681365
  • Title

    Expanding the structure of shunting inhibitory artificial neural network classifiers

  • Author

    Arulampalam, Ganesh ; Bouzerdoum, Abdesselam

  • Author_Institution
    Edith Cowan Univ., Joondalup, WA, Australia
  • Volume
    3
  • fYear
    2002
  • fDate
    6/24/1905 12:00:00 AM
  • Firstpage
    2855
  • Lastpage
    2860
  • Abstract
    Shunting inhibitory artificial neural networks (SIANNs) are biologically inspired networks in which the neurons interact via a nonlinear mechanism called shunting inhibition. They are capable of producing complex, nonlinear decision boundaries. The structure and operation of feedforward SIANNs and some enhancements are presented. They are applied to several classification problems, and their performance is compared to that of the multilayer perceptron classifier
  • Keywords
    feedforward neural nets; pattern classification; biologically inspired networks; complex nonlinear decision boundaries; feedforward SIANN; shunting inhibitory artificial neural network classifier structure expansion; Adaptive control; Artificial neural networks; Australia; Cellular neural networks; Differential equations; Gain control; Image processing; Multilayer perceptrons; Neurons; Programmable control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
  • Conference_Location
    Honolulu, HI
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-7278-6
  • Type

    conf

  • DOI
    10.1109/IJCNN.2002.1007601
  • Filename
    1007601