Volume 446, Number 1, January IV 2006
|Page(s)||395 - 402|
|Published online||09 January 2006|
Automatic classification of eclipsing binaries light curves using neural networks
Dpt. de Inteligencia Artificial, U.N.E.D., c/ Juan del Rosal, 16, 28040 Madrid, Spain e-mail: firstname.lastname@example.org
2 Laboratorio de Astrofísica Espacial y Física Fundamental, PO Box 50727, 28080 Madrid, Spain
3 XMM-Newton SOC, ESAC, PO Box 50727, 28080 Madrid, Spain e-mail: Celia.Sanchez@sciops.esa.int
4 Research and Scientific Support Department, ESA, ESTEC, Postbus 299, 2200 AG Noordwijk, The Netherlands e-mail: email@example.com
Accepted: 26 August 2005
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 systems 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.
Key words: stars: binaries: eclipsing / stars: binaries: general / methods: data analysis / methods: statistical
© ESO, 2006
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