Convergence suppression and divergence facilitation: new approach to prune hidden layer and weights of feedforward neural networks
S. Yasui, Aleksander Malinowski, Jacek M. Żurada · 2002
A pruning algorithm is devised for multilayer multi-output feedforward perceptron networks. The algorithm efficiently reduces the total number of hidden units and the number of weights in the output layer. Test examples include network pruning for the IRIS classifier and for the bitmap digit classifier.