Title :
Adaptive class-specific partitioning as a means of initializing RBF-networks
Author :
Kestler, H.A. ; Schwenker, F. ; Höher, M. ; Palm, G.
Author_Institution :
Dept. of Neural Inf. Process., Ulm Univ., Germany
Abstract :
In this paper a strategy for neural network training is described. The similarities of supervised competitive and gradient descent learning are used to construct an algorithm which initializes radial basis function networks
Keywords :
adaptive systems; character recognition; feedforward neural nets; learning (artificial intelligence); adaptive class-specific partitioning; character recognition; gradient descent learning; neural network; radial basis function networks; supervised competitive learning; Data compression; Feedforward neural networks; Information processing; Kernel; Neural networks; Neurons; Phase estimation; Prototypes; Radial basis function networks; Supervised learning;
Conference_Titel :
Systems, Man and Cybernetics, 1995. Intelligent Systems for the 21st Century., IEEE International Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-2559-1
DOI :
10.1109/ICSMC.1995.537731
