Radial basis function neural network based on order statistics

Jose A. Moreno-Escobar, Francisco J. Gallegos-Funes, Volodymyr Ponomaryov, Jose M. De-la-Rosa-Vazquez

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

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.

Original languageEnglish
Title of host publicationMICAI 2007
Subtitle of host publicationAdvances in Artificial Intelligence - 6th Mexican International Conference on Artificial Intelligence, Proceedings
PublisherSpringer Verlag
Pages150-160
Number of pages11
ISBN (Print)9783540766308
DOIs
StatePublished - 2007
Event6th Mexican International Conference on Artificial Intelligence, MICAI 2007 - Aguascalientes, Mexico
Duration: 4 Nov 200710 Nov 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4827 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference6th Mexican International Conference on Artificial Intelligence, MICAI 2007
Country/TerritoryMexico
CityAguascalientes
Period4/11/0710/11/07

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