DocumentCode
982785
Title
Neural network design using Voronoi diagrams
Author
Bose, N.K. ; Garga, Amulya K.
Author_Institution
Dept. of Electr. & Comput. Eng., Pennsylvania State Univ., University Park, PA, USA
Volume
4
Issue
5
fYear
1993
fDate
9/1/1993 12:00:00 AM
Firstpage
778
Lastpage
787
Abstract
A novel approach is proposed which determines the number of layers, the number of neurons in each layer, and their connection weights for a particular implementation of a neural network, with the multilayer feedforward topology, designed to classify patterns in the multidimensional feature space. The approach is based on construction of a Voronoi diagram over the set of points representing patterns in feature space and this finds added usefulness in deriving alternate neural network structures for realizing the desired pattern classification
Keywords
computational geometry; feedforward neural nets; pattern recognition; topology; Voronoi diagrams; connection weights; design; multidimensional feature space; multilayer feedforward topology; neural network; pattern classification; Artificial neural networks; Feedforward neural networks; Iterative algorithms; Multi-layer neural network; Multidimensional systems; Network topology; Neural networks; Neurons; Pattern classification; Systems engineering and theory;
fLanguage
English
Journal_Title
Neural Networks, IEEE Transactions on
Publisher
ieee
ISSN
1045-9227
Type
jour
DOI
10.1109/72.248455
Filename
248455
Link To Document