Title :
Neural network basis function center selection using cluster analysis
Author :
Warwick, K. ; Mason, J.D. ; Sutanto, E.L.
Author_Institution :
Dept. of Cybern., Reading Univ., UK
Abstract :
This paper deals with the selection of centres for radial basis function (RBF) networks. A novel mean-tracking clustering algorithm is described as a way in which centers can be chosen based on a batch of collected data. A direct comparison is made between the mean-tracking algorithm and k-means clustering and it is shown how mean-tracking clustering is significantly better in terms of achieving an RBF network which performs accurate function modelling
Keywords :
approximation theory; convergence of numerical methods; feedforward neural nets; function approximation; basis function center selection; cluster analysis; convergence; function modelling; mean-tracking clustering; radial basis function networks; Clustering algorithms; Control systems; Cybernetics; Electrical capacitance tomography; Equations; Input variables; Neural networks; Radial basis function networks; Robust stability; Signal mapping;
Conference_Titel :
American Control Conference, Proceedings of the 1995
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-2445-5
DOI :
10.1109/ACC.1995.533845
