• DocumentCode
    2695609
  • Title

    Self-organizing hierarchical feature maps

  • Author

    Koikkalainen, Pasi ; Oja, Erkki

  • fYear
    1990
  • fDate
    17-21 June 1990
  • Firstpage
    279
  • Abstract
    The topological feature map (TFM) algorithm introduced by T. Kohenen (1982) implements two important properties: a vector quantization (VQ) and a topology-preserving mapping. A tree-structured TFM (TSTFM) is presented as a computationally inexpensive alternative to the TFM algorithm. The computational complexity of the TSTFM is O (log N) rather than O(N) for the TFM. In addition, the TSTFM has some new properties that prove to be useful for VQ and in the context of visual perception: increased performance in VQ compared to the tree-structured VQ of A. Buzo et al. (1980) and hierarchical mapping of code vectors
  • Keywords
    computational complexity; neural nets; self-adjusting systems; TFM algorithm; computational complexity; neural nets; self-organising hierarchical feature maps; topological feature map; topology-preserving mapping; tree-structured TFM; unsupervised learning; vector quantization; visual perception;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1990., 1990 IJCNN International Joint Conference on
  • Conference_Location
    San Diego, CA, USA
  • Type

    conf

  • DOI
    10.1109/IJCNN.1990.137727
  • Filename
    5726686