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.
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Moreno-Escobar, J.A., Gallegos-Funes, F.J., Ponomaryov, V., de-la-Rosa-Vazquez, J.M. (2007). Radial Basis Function Neural Network Based on Order Statistics. In: Gelbukh, A., Kuri Morales, Á.F. (eds) MICAI 2007: Advances in Artificial Intelligence. MICAI 2007. Lecture Notes in Computer Science(), vol 4827. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76631-5_15
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DOI: https://doi.org/10.1007/978-3-540-76631-5_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-76630-8
Online ISBN: 978-3-540-76631-5
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