• DocumentCode
    3112588
  • Title

    Neural network techniques in electromagnetic target classification: a comparison study

  • Author

    Turhan-Sayan, G. ; Ince, T.

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Middle East Tech. Univ., Ankara, Turkey
  • Volume
    4
  • fYear
    1999
  • fDate
    11-16 July 1999
  • Firstpage
    2222
  • Abstract
    The performances of a self-organizing map classifier, a multilayer perceptron classifier and a conventional classifier, based on the well-known principal component analysis technique, are compared in classifying a group of model aircraft, according to their accuracy and their real-time classification speed.
  • Keywords
    aircraft; multilayer perceptrons; pattern classification; principal component analysis; radar computing; radar signal processing; self-organising feature maps; electromagnetic target classification; model aircraft; multilayer perceptron classifier; neural network techniques; performance; principal component analysis technique; self-organizing map classifier; Aircraft; Artificial neural networks; Clustering algorithms; Electromagnetic scattering; Frequency; Intelligent networks; Multi-layer neural network; Neural networks; Principal component analysis; Spatial databases;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Antennas and Propagation Society International Symposium, 1999. IEEE
  • Conference_Location
    Orlando, FL, USA
  • Print_ISBN
    0-7803-5639-x
  • Type

    conf

  • DOI
    10.1109/APS.1999.789251
  • Filename
    789251
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3112588