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A two-stage procedure for the training of radial neural networks in pattern recognition is considered. At the first stage, the set of training samples is split into subsets and the class centers are adjusted for them. Then the parameters of the radial functions are adjusted for each subset of the training samples. The coefficients of contingency of the vectors of attributes of training samples are used to form subsets.
neural network, pattern recognition, radial function, vector of attribute.
Fursov VA, Kozin NE. Stage-wise learning of radial neural networks. Computer Optics 2004; 26: 138-141.
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