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J/A+A/538/A76 Stellar spectra automatic spectral classification (Navarro+, 2012)
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Beginning of ReadMe :J/A+A/538/A76 Automatic stellar spectral classification (Navarro+, 2012)
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Automatic spectral classification of stellar spectra with low signal-to-noise
ratio using artificial neural networks.
Navarro S.G., Corradi R.L.M., Mampaso A.
<Astron. Astrophys., 538, A76 (2012)>
=2012A&A...538A..76N
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ADC_Keywords: Planetary nebulae ; MK spectral classification
Keywords: methods: data analysis - planetary nebulae: general -
astronomical databases: miscellaneous
Abstract:
As part of a project aimed at deriving extinction-distances for
thirty-five planetary nebulae, spectra of a few thousand stars were
analyzed to determine their spectral type and luminosity class.
We present here the automatic spectral classification process used to
classify stellar spectra. This system can be used to classify any
other stellar spectra with similar or higher signal-to-noise ratios.
Spectral classification was performed using a system of artificial
neural networks that were trained with a set of line-strength indices
selected among the spectral lines most sensitive to temperature and
the best luminosity tracers. The training and validation processes of
the neural networks are discussed and the results of additional
validation probes, designed to ensure the accuracy of the spectral
classification, are presented.
Description:
More than 2000 stars distributed in the field of view of 35 planetary
nebulae, and 31 stars from the spectral catalog of Jacoby et al.
(1984, Cat. III/92) were observed with the LDSS2 (Low Dispersion
Survey Spectrograph) at the William Herschel Telescope (WHT) on La
Palma, Spain.