• DocumentCode
    2175276
  • Title

    A kind of neural network similar to ART network with application to radar signal sorting

  • Author

    Tang, Jinsong ; Zhu, Zhaoda

  • Author_Institution
    Nanjing Univ. of Aeronaut. & Astronaut., China
  • fYear
    1994
  • fDate
    23-27 May 1994
  • Firstpage
    398
  • Abstract
    In order to solve the problem of radar signal sorting in real time, this paper presents a kind of neural network (NN) similar to ART network. Its characteristic is to finish heuristic clustering algorithm of pattern recognition by using adaptive resonance theory (ART) on the basis of making good use of data statistic property. This NN has not the self-stabilized top-down structure of the general ART network. The self-stabilized learning is finished by bottom-up structure. Although this NN has less adaptability than ART NN, it can solve a wide variety of problems as well. The vigilance and weight updating have more strict mathematical formulas. The result of digital simulation shows this network can work well in sorting radar signals. It can also be used to solve the similar problem of clustering
  • Keywords
    heuristic programming; neural nets; radar theory; signal processing; ART network; adaptive resonance theory; data statistic property; heuristic clustering algorithm; neural network; pattern recognition; radar signal sorting; self-stabilized top-down structure; vigilance; weight updating; Clustering algorithms; Digital simulation; Heuristic algorithms; Neural networks; Pattern recognition; Radar; Resonance; Sorting; Statistics; Subspace constraints;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Aerospace and Electronics Conference, 1994. NAECON 1994., Proceedings of the IEEE 1994 National
  • Conference_Location
    Dayton, OH
  • Print_ISBN
    0-7803-1893-5
  • Type

    conf

  • DOI
    10.1109/NAECON.1994.332871
  • Filename
    332871