Error Back Propagation Algorithm with Adaptive Learning Rate

Error Back Propagation algorithm is one of the most popular method for training artificial neural networks. Unfortunately, this is also one of the slowest due to constant and small learning rate parameter used to update weights of neurons. There are therefore many methods for dynamic change this par...

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Bibliographic Details
Published in:The International Conference on Information and Digital Technologies (Online) pp. 216 - 222
Main Authors: Kolbusz, Janusz, Rozycki, Pawel, Lysenko, Oleksandr, Wilamowski, Bogdan M.
Format: Conference Proceeding
Language:English
Published: IEEE 01.06.2019
Subjects:
Adaptive learning
Approximation algorithms
Artificial neural networks
Backpropagation
EBP algorithm
Estimation
gradient descent
Heuristic algorithms
learning rate estimation
Neurons
Training
ISSN:2575-677X
Online Access:Get full text
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Summary:Error Back Propagation algorithm is one of the most popular method for training artificial neural networks. Unfortunately, this is also one of the slowest due to constant and small learning rate parameter used to update weights of neurons. There are therefore many methods for dynamic change this parameter in the adaptive manner. In this paper has been presented new method based on estimation of learning rate with respect of approximation for the value of output error.
ISSN:2575-677X
DOI:10.1109/DT.2019.8813440