Near-optimal dynamic learning rate for training backpropagation neural networks

Serge Roy

doi:10.1117/12.152627

19 August 1993 Near-optimal dynamic learning rate for training backpropagation neural networks

Serge Roy

Proceedings Volume 1966, Science of Artificial Neural Networks II; (1993) https://doi.org/10.1117/12.152627
Event: Optical Engineering and Photonics in Aerospace Sensing, 1993, Orlando, FL, United States

Abstract

Back-propagation neural networks is a very popular training algorithm for neural nets. One of the problems with this learning algorithm is its training speed. The selection of a good learning rate is a very important factor to achieve a satisfactory learning time. However, it is very difficult to determine an optimal learning rate since this parameter is dependent on a lot of variables such as the size of the network, the number of examples in the training sets... A new method is proposed to compute a near optimal learning rate for a three layer (one hidden layer) back propagation network.

Citation Download Citation

Serge Roy "Near-optimal dynamic learning rate for training backpropagation neural networks", Proc. SPIE 1966, Science of Artificial Neural Networks II, (19 August 1993); https://doi.org/10.1117/12.152627

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