Radial basis function neural network based on order statistics

Authors:
Jose A. Moreno-Escobar;Francisco J. Gallegos-Funes;Volodymyr Ponomaryov;Jose M. De-La-Rosa-Vazquez
Affiliations:
National Polytechnic Institute of Mexico, Mechanical and Electrical Engineering Higher School, Mexico, D. F., Mexico;National Polytechnic Institute of Mexico, Mechanical and Electrical Engineering Higher School, Mexico, D. F., Mexico;National Polytechnic Institute of Mexico, Mechanical and Electrical Engineering Higher School, Mexico, D. F., Mexico;National Polytechnic Institute of Mexico, Mechanical and Electrical Engineering Higher School, Mexico, D. F., Mexico
Venue:
MICAI'07 Proceedings of the artificial intelligence 6th Mexican international conference on Advances in artificial intelligence
Year:
2007

Citing 11
Cited 1

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Abstract

In this paper we present a new type of Radial Basis Function (RBF) Neural Network based in order statistics for image classification applications. The proposed neural network uses the Median M-type (MM) estimator in the scheme of radial basis function to train the neural network. The proposed network is less biased by the presence of outliers in the training set and was proved an accurate estimation of the implied probabilities. From simulation results we show that the proposed neural network has better classification capabilities in comparison with other RBF based algorithms.