Automatic spectral classification of stellar spectra with low signal-to-noise ratio using artificial neural networks

Computer Science – Databases

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Methods: Data Analysis, Planetary Nebulae: General, Astronomical Databases: Miscellaneous

Scientific paper

Context. 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. Aims: 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. Methods: 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. Results: Our system permits the classification of stellar spectra of signal-to-noise ratio (S/N) significantly lower than it is generally considered to be needed. For S/N ≥ 20, a precision generally better than two spectral subtypes is obtained. At S/N < 20, classification is still possible but has a lower precision. Its potential to identify peculiar sources, such as emission-line stars, is also recognized.
Based on observations obtained at the 4.2 m WHT telescope of the Isaac Newton Group of Telescopes in the Spanish Observatorio del Roque de Los Muchachos of the Instituto de Astrofísica de Canarias.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Automatic spectral classification of stellar spectra with low signal-to-noise ratio using artificial neural networks does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Automatic spectral classification of stellar spectra with low signal-to-noise ratio using artificial neural networks, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Automatic spectral classification of stellar spectra with low signal-to-noise ratio using artificial neural networks will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-887398

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.