@inproceedings{7e6dc463c49a45ca94bc6eadbb759855,
title = "A Frobenius approximation reduction method (FARM) for determining optimal number of hidden units",
abstract = "A least square approximation method is proposed to reduce the number of hidden units of a trained multilayer perceptron artificial neural network structure. In this method, hidden neurons contributing the most to the net function of the output layer will be retained while the hidden units contributing the least will be removed. It is shown theoretically that the proposed method minimizes the Frobenius norm of the approximation error, hence the name Frobenius approximation reduction method (FARM). Also reported are simulation results on ECG (electrocardiogram) classifications. The results support the theoretical predictions and yield very encouraging performances.",
author = "Kung, {S. Y.} and Hu, {Yu Hen}",
year = "1992",
language = "English (US)",
isbn = "0780301641",
series = "Proceedings. IJCNN - International Joint Conference on Neural Networks",
publisher = "Publ by IEEE",
pages = "163--168",
editor = "Anon",
booktitle = "Proceedings. IJCNN - International Joint Conference on Neural Networks",
note = "International Joint Conference on Neural Networks - IJCNN-91-Seattle ; Conference date: 08-07-1991 Through 12-07-1991",
}