• DocumentCode
    3186857
  • Title

    The detection theory of self-organizing feature map and its application

  • Author

    HuangFu Kan ; Wan Jian Wei

  • fYear
    1992
  • fDate
    18-22 May 1992
  • Firstpage
    108
  • Abstract
    Artificial neural network models have previously been studied in the hope of achieving human-like performance in the field of information processing. The optimized learning rule, based on the Kohonen self-organizing feature map, is modified in order to decrease the fuzziness on the edges of the topological neighbors. The authors describe the mathematical mechanisms of multidimensional detection, and its application in a radar system. High-accuracy performance is achieved, and detection is nonparametric because of the self-organizing learning process
  • Keywords
    edge detection; learning (artificial intelligence); neural nets; radar theory; self-organising feature maps; Kohonen; detection theory; edges; fuzziness; information processing; multidimensional detection; nonparametric detection; radar; self-organizing feature map; self-organizing learning; topological neighbors; Artificial neural networks; Associative memory; Biological neural networks; Gravity; Humans; Information processing; Neurons; Organizing; Probability distribution; Stochastic processes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Aerospace and Electronics Conference, 1992. NAECON 1992., Proceedings of the IEEE 1992 National
  • Conference_Location
    Dayton, OH
  • Print_ISBN
    0-7803-0652-X
  • Type

    conf

  • DOI
    10.1109/NAECON.1992.220660
  • Filename
    220660