Clustering with multilayer perceptrons and self-organized (Hebbian) learning

Authors:
Jugurta R. Montalvão Filho;Eduardo O. Freire;Murilo A. Bezerra, Jr.
Affiliations:
(Correspd. jmontalvao@ufs.br) Universidade Federal de Sergipe (UFS), São Cristóvão, CEP. 49100-000, Brazil;Universidade Federal de Sergipe (UFS), São Cristóvão, CEP. 49100-000, Brazil;Universidade Federal de Sergipe (UFS), São Cristóvão, CEP. 49100-000, Brazil
Venue:
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - VIII Brazilian Symposium on Neural Networks
Year:
2007

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Abstract

A new local (Hebbian) learning algorithm for artificial neurons is presented. It is shown that, in spite of its implementation simplicity, this new algorithm, applied to neurons with sigmoidal activation function, performs data clustering by finding valleys of the probability density function (PDF) of the multivariate random variables that model incoming data. Some interesting features of this new algorithm are illustrated by some experiments based on both artificial data and real world data.