A new hybrid fuzzy ARTMAP and radial basis function neural network with online pruning strategy

In this paper, a new online learning algorithm is proposed to learn a data sample in hybrid mode. This new algorithm is developed and referred as Growing and Pruning - Fuzzy ARTMAP-radial basis function (GAP-FAM-RBF) neural network. In this algorithm, fuzzy ARTMAP (FAM) network learns from training...

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Bibliographic Details
Published in:	2016 7th IEEE Control and System Graduate Research Colloquium (ICSGRC) pp. 17 - 21
Main Authors:	Shoun Ying Leow, Shen Yuong Wong, Keem Siah Yap, Hwa Jen Yap
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01-08-2016
Subjects:	Biological neural networks Control systems fuzzy ARTMAP (FAM) Neurons online learning pruning Radial Basis Function Radial basis function networks regression Testing Training Training data
Online Access:	Get full text
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Summary:	In this paper, a new online learning algorithm is proposed to learn a data sample in hybrid mode. This new algorithm is developed and referred as Growing and Pruning - Fuzzy ARTMAP-radial basis function (GAP-FAM-RBF) neural network. In this algorithm, fuzzy ARTMAP (FAM) network learns from training samples and radial basis function (RBF) network provides viable solutions. The GAP-FAM-RBF that proposed is able to learn online from the first data samples. The insignificant hidden neurons will be pruned. The performance of this algorithm is evaluated on regression applications.
DOI:	10.1109/ICSGRC.2016.7813294