• DocumentCode
    1908694
  • Title

    Quantized, piecewise linear filter network

  • Author

    Sørensen, John Aasted

  • Author_Institution
    Tech. Univ. of Denmark, Lyngby, Denmark
  • fYear
    1993
  • fDate
    6-9 Sep 1993
  • Firstpage
    470
  • Lastpage
    474
  • Abstract
    A quantization based piecewise linear filter network is defined. A method for the training of this network based on local approximation in the input space is devised. The training is carried out by repeatedly alternating between vector quantization of the training set into quantization classes and equalization of the quantization classes linear filter mean square training errors. The equalization of the mean square training errors is carried out by adapting the boundaries between neighbor quantization classes such that the differences in mean square training errors are reduced
  • Keywords
    approximation theory; filtering theory; learning (artificial intelligence); neural nets; vector quantisation; input space; linear filter mean square training errors; local approximation; quantization based piecewise linear filter network; quantization classes; vector quantization; Error correction; Mean square error methods; Nonlinear filters; Piecewise linear approximation; Piecewise linear techniques; Tree data structures; Vector quantization; Wiener filter;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks for Processing [1993] III. Proceedings of the 1993 IEEE-SP Workshop
  • Conference_Location
    Linthicum Heights, MD
  • Print_ISBN
    0-7803-0928-6
  • Type

    conf

  • DOI
    10.1109/NNSP.1993.471841
  • Filename
    471841