P.P. Van der Smagt, Minimisation methods for training feedforward neural networks, Neural Networks, 7:(1), 1-11, 1993


Abstract - Minimisation methods for training feed-forward networks with back-propagation are compared. Feed-forward neural network training is a special case of function minimisation, where no explicit model of the data is assumed. Therefore, and due to the high dimensionality of the data, linearisation of the training problem through use of orthogonal basis functions is not desirable. The focus is on function minimisation on any basis