Abstract
In this paper we describe a fast procedure for retraining a feedforward network, previously trained by error backpropagation, following a small change in the training data. This technique would permit fine calibration of individual neural network based control systems in a mass-production environment. We also derive a generalised error backpropagation algorithm which allows an exact evaluation of all of the terms in the Hessian matrix. The fast retraining procedure is illustrated using a simple example.
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