A&A 446, 395-402 (2006)
DOI: 10.1051/0004-6361:20052830
Automatic classification of eclipsing binaries light curves using neural networks
L. M. Sarro1, C. Sánchez-Fernández2, 3 and Á. Giménez41 Dpt. de Inteligencia Artificial, U.N.E.D., c/ Juan del Rosal, 16, 28040 Madrid, Spain
e-mail: lsb@dia.uned.es
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: agimenez@rssd.esa.int
(Received 7 February 2005 / Accepted 26 August 2005)
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
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
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