• DocumentCode
    285314
  • Title

    Neural network design using Voronoi diagrams: preliminaries

  • Author

    Bose, N.K. ; Garga, A.K.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Pennsylvania State Univ., University Park, PA, USA
  • Volume
    3
  • fYear
    1992
  • fDate
    7-11 Jun 1992
  • Firstpage
    127
  • Abstract
    A novel approach based on the construction of a Voronoi diagram is proposed to determine the number of layers, the number of neurons in each layer, and their connection weights for a particular implementation of a neural network. The neural network has a multilayer feedforward topology, and is designed to classify patterns in the multidimensional feature space. To illustrate the procedure, an example is given of the classification of patterns that are not linearly separable in feature space
  • Keywords
    computational geometry; feedforward neural nets; pattern recognition; Voronoi diagram; multidimensional feature space; multilayer feedforward topology; neural network design; pattern classification; Artificial neural networks; Computational geometry; Feedforward neural networks; Multi-layer neural network; Multidimensional systems; Network topology; Neural networks; Neurons; Nonlinear equations; Systems engineering and theory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1992. IJCNN., International Joint Conference on
  • Conference_Location
    Baltimore, MD
  • Print_ISBN
    0-7803-0559-0
  • Type

    conf

  • DOI
    10.1109/IJCNN.1992.227181
  • Filename
    227181