• DocumentCode
    2430614
  • Title

    A new quantitative measure of topology preservation in Kohonen´s feature maps

  • Author

    Villmann, Th. ; Der, R. ; Martinetz, Th

  • Author_Institution
    Inst. of Inf., Leipzig Univ., Germany
  • Volume
    2
  • fYear
    1994
  • fDate
    27 Jun-2 Jul 1994
  • Firstpage
    645
  • Abstract
    In this paper we give a new approach for quantifying topology preservation using explicitly the structure of the data manifold. It can be applied to linear and nonlinear data manifolds M. Further, this method allows one to quantify the range of folds. Our approach employs what we call the topographic function, which is defined based on the so called masked Voronoi polyhedra introduced by Martinetz (1993) for defining neighbourhood and topology preservation of feature maps
  • Keywords
    learning (artificial intelligence); self-organising feature maps; topology; Kohonen´s feature maps; data manifold; masked Voronoi polyhedra; quantitative measure; topographic function; topology preservation; Euclidean distance; Graphics; Informatics; Lattices; Particle measurements; Research and development; Robots; Topology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
  • Conference_Location
    Orlando, FL
  • Print_ISBN
    0-7803-1901-X
  • Type

    conf

  • DOI
    10.1109/ICNN.1994.374251
  • Filename
    374251