Median M-type radial basis function neural network

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Abstract

In this paper we present the capability of the Median M-Type Radial Basis Function (MMRBF) Neural Network in 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. Other RBF based algorithms were compared with our approach. From simulation results we observe that the MMRBF neural network has better classification capabilities.

Original languageEnglish
Title of host publicationProgress in Pattern Recognition, Image Analysis and Applications - 12th Iberoamerican Congress on Pattern Recognition, CIARP 2007, Proceedings
Pages525-533
Number of pages9
StatePublished - 2007
Event12th Iberoamerican Congress on Pattern Recognition, CIARP 2007 - Vina del Mar-Valparaiso, Chile
Duration: 13 Nov 200716 Nov 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4756 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference12th Iberoamerican Congress on Pattern Recognition, CIARP 2007
Country/TerritoryChile
CityVina del Mar-Valparaiso
Period13/11/0716/11/07

Keywords

  • Neural networks
  • Radial basis functions
  • Rank M-type estimators

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