Title :
Clustering with multilayer perceptrons and hebbian learning based on kullback-leibler divergence
Author :
Filho, Jugurt R Montalvão ; Bezerra, Murilo A., Jr. ; Oliveira, Levi P.
Author_Institution :
Lab. Automacao, Univ. Tiradentes, Aracaju
fDate :
Sept. 29 2004-Oct. 1 2004
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 presented and illustrated by practical experiments
Keywords :
Hebbian learning; multilayer perceptrons; pattern clustering; Hebbian learning; Kullback-Leibler divergence; artificial neurons; data clustering; multilayer perceptrons; multivariate random variables; probability density function; sigmoidal activation function; Annealing; Clustering algorithms; Cost function; Hebbian theory; Multilayer perceptrons; Neural networks; Neurons; Probability density function; Prototypes; Random variables;
Conference_Titel :
Machine Learning for Signal Processing, 2004. Proceedings of the 2004 14th IEEE Signal Processing Society Workshop
Conference_Location :
Sao Luis
Print_ISBN :
0-7803-8608-4
DOI :
10.1109/MLSP.2004.1422980
