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Centre and Variance Selection for Gaussian Radial Basis Function Artificial Neural Networks

  • F. Scheibel
  • N. C. Steele
  • R. Low
Conference paper

Abstract

The quality of the response of a RBF neural network depends strongly on the calculation method of the centres and the variance matrices. This paper describes an algorithm which combines the calculation of the centres and variances of the Gaussian nodes to improve the response of a RBF neural network. The selection of the centres is made using a modified version of the K-means algorithm and the variances are based on the sample variance-covariance matrices of the input values associated with the centres. Applications to classification and function approximation problems are considered.

Keywords

Hide Layer Fuzzy Controller Output Node Fuzzy Cluster Centre Vector 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Wien 1999

Authors and Affiliations

  • F. Scheibel
    • 1
  • N. C. Steele
    • 2
  • R. Low
    • 2
  1. 1.Fachhochschule DarmstadtDarmstadtGermany
  2. 2.Coventry UniversityCoventryUK

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