On-line backpropagation in two-layered neural networks
Peter Riegler, Michael L. Biehl · Journal of Physics A Mathematical and General · 1995
We present an exact analysis of learning a rule by on-line gradient descent in a two-layered neural network with adjustable hidden-to-output weights (backpropagation of error). Results are compared with the training of networks having the same architecture but fixed weights in the second layer.