Unified formulation for training recurrent networks with derivative adaptive critics
L.A. Feldkamp, G.V. Puskorius, Danil V. Prokhorov · Proceedings of International Conference on Neural Networks (ICNN'97) · 2002
We present a procedure for obtaining the derivatives used in training a recurrent network that combines in a unified framework the techniques of backpropagation through time and derivative adaptive critics. The resulting formulation is consistent with previous descriptions, but has the advantage of allowing the mentioned techniques to be used together in a proportion that is appropriate to a given problem.