A FAST PROCEDURE FOR RETRAINING THE MULTILAYER PERCEPTRON

Author:

Bishop Chris1

Affiliation:

1. Neural Networks Group, AEA Technology, Harwell Laboratory, Oxfordshire OX11 0RA, UK

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.

Publisher

World Scientific Pub Co Pte Lt

Subject

Computer Networks and Communications,General Medicine

Cited by 14 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. The Hessian by blocks for neural network by backward propagation;Journal of Taibah University for Science;2024-04-23

2. Research and application of RBF neural network based on modified Levenberg-Marquardt;Journal of Computational Methods in Sciences and Engineering;2022-09-05

3. Stability Analysis of the Modified Levenberg–Marquardt Algorithm for the Artificial Neural Network Training;IEEE Transactions on Neural Networks and Learning Systems;2021-08

4. Exact Hessian Matrix Calculation for Complex-Valued Neural Networks;Soft Computing Applications;2015-11-03

5. Reaction kinetics determination and neural networks modeling of methanol dehydration over nano γ-Al2O3 catalyst;Journal of Industrial and Engineering Chemistry;2012-11

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