• DocumentCode
    1843678
  • Title

    An empirical study of neighbourhood decay in Kohonen´s self organising map

  • Author

    Keith-Magee, Russell ; Venkatesh, Svetha ; Takatsuka, Masahiro

  • Author_Institution
    Sch. of Comput., Curtin Univ. of Technol., Perth, WA, Australia
  • Volume
    3
  • fYear
    1999
  • fDate
    1999
  • Firstpage
    1953
  • Abstract
    In this paper, empirical results are presented which suggest that size and rate of decay of region size plays a much more significant role in the learning, and especially the development of topographic feature maps. Using these results as a basis, a scheme for decaying region size during SOM training is proposed. The proposed technique provides near optimal training time. This scheme avoids the need for sophisticated learning gain decay schemes, and precludes the need for a priori knowledge of likely training times. This scheme also has some potential uses for continuous learning
  • Keywords
    curve fitting; learning (artificial intelligence); optimisation; self-organising feature maps; topology; Kohonen self organising map; SOM learning; continuous learning; decaying region size; gain decay; goodness of fit; neighbourhood decay; optimisation; topographic feature maps; Algorithm design and analysis; Biological processes; Biological system modeling; Biology computing; Brain modeling; Geography; Graphics; Iterative algorithms; Performance analysis; Performance gain;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1999. IJCNN '99. International Joint Conference on
  • Conference_Location
    Washington, DC
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-5529-6
  • Type

    conf

  • DOI
    10.1109/IJCNN.1999.832682
  • Filename
    832682