Wavelet Based Feature Extraction for Clustering of Be Stars

0424303 - ASÚ 2014 RIV CZ eng C - Conference Paper (international conference)
Bromová, P. - Škoda, Petr - Zendulka, J.
Wavelet Based Feature Extraction for Clustering of Be Stars.
Nostradamus 2013: Prediction, Modeling and Analysis of Complex Systems. Vol. 210. Cham: Springer, 2013 - (Zelinka, I.; Chen, G.; Rossler, O.; Snášel, V.; Abraham, A.), s. 467-474. ISBN 978-3-319-00541-6. ISSN 2194-5357.
[Nostradamus 2013. Ostrava (CZ), 03.06.2013-05.06.2013]
Institutional support: RVO:67985815
Keywords : feature extraction * stellar spectra * wavelet transform
Subject RIV: BN - Astronomy, Celestial Mechanics, Astrophysics

The goal of our work is to create a feature extraction method for classification of Be stars. Be stars are characterized by prominent emission lines in their spectrum. We focus on the automated classification of Be stars based on typical shapes of their emission lines. We aim to design a reduced, specific set of features characterizing and discriminating the shapes of Be lines. In this paper, we present a feature extraction method based on the wavelet transform and its power spectrum. Both the discrete and continuous wavelet transform are used. Different feature vectors are created and compared on clustering of Be stars spectra from the archive of the Astronomical Institute of the Academy of Sciences of the Czech Republic. The clustering is performed using the kmeans algorithm. The results of our method are promising and encouraging to more detailed analysis.
Permanent Link: http://hdl.handle.net/11104/0230521