Automatic classification of eclipsing binaries light curves using neural networks
Abstract
In this work we present a system for the automatic classification of the light curves of eclipsing binaries. This system is based on a classification scheme that aims to separate eclipsing binary sistems according to their geometrical configuration in a modified version of the traditional classification scheme. The classification is performed by a Bayesian ensemble of neural networks trained with Hipparcos data of seven different categories including eccentric binary systems and two types of pulsating light curve morphologies.
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