Exact Learning Curves for EKF Training
We formulate a learning algorithm for online learning in neural networks using the principles of the Extended Kaiman Filter approach. This gives rise to a Bayesian learning scheme where the learning rate parameter is adapted automatically. The approach is applied to regression problems whereby the rule to be learned is non-stationary, examining both linear and nonlinear cases.