• DocumentCode
    1647670
  • Title

    The plastic self organising map

  • Author

    Lang, Robert ; Warwick, Kevion

  • Author_Institution
    Dept. of Cybern., Reading Univ., UK
  • Volume
    1
  • fYear
    2002
  • fDate
    6/24/1905 12:00:00 AM
  • Firstpage
    727
  • Lastpage
    732
  • Abstract
    A novel extension to Kohonen´s self-organising map, called the plastic self organising map (PSOM), is presented. PSOM is unlike any other network because it only has one phase of operation. The PSOM does not go through a training cycle before testing, like the SOM does and its variants. Each pattern is thus treated identically for all time. The algorithm uses a graph structure to represent data and can add or remove neurons to learn dynamic nonstationary pattern sets. The network is tested on a real world radar application and an artificial nonstationary problem
  • Keywords
    graph theory; learning (artificial intelligence); pattern classification; self-organising feature maps; Kohonen self-organising map; graph structure; online training algorithm; passive radar; pattern classification; plastic self organising map; Artificial neural networks; Clustering algorithms; Cybernetics; Data visualization; Labeling; Neural networks; Neurons; Plastics; Radar applications; Testing;
  • 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.2002.1005563
  • Filename
    1005563