• DocumentCode
    1907855
  • Title

    An extended self-organizing map with gated neurons

  • Author

    Chandrasekaran, V. ; Palaniswami, M. ; Caelli, Terry M.

  • Author_Institution
    Sch. of Inf. Technol. & Electr. Eng., Melbourne Univ., Parkville, Vic., Australia
  • fYear
    1993
  • fDate
    1993
  • Firstpage
    1474
  • Abstract
    Kohonen´s self-organizing map is extended by a technique allowing the neurons in the feature map to compete in a selective manner. This is accomplished by introducing gated neurons prior to the winner-take-all layer. These gated neurons are activated by a cosine function with time-varying frequency. This results in a spatio-temporal signature at the output for each input pattern over a predetermined interval. This pattern is found to be unique in its characteristics and leads to very high degree of recognition results. The simulations performed on a standard texture recognition problem indicate excellent performance
  • Keywords
    image recognition; self-organising feature maps; vector quantisation; Kohonen´s self-organizing map; cosine function; feature map; gated neurons; spatio-temporal signature; texture recognition; time-varying frequency; winner-take-all layer; Computer architecture; Frequency; Information technology; Neural networks; Neurons; Pattern classification; Pattern recognition; Self organizing feature maps; Signal processing; Supervised learning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1993., IEEE International Conference on
  • Conference_Location
    San Francisco, CA
  • Print_ISBN
    0-7803-0999-5
  • Type

    conf

  • DOI
    10.1109/ICNN.1993.298774
  • Filename
    298774