Automated classification of ELODIE stellar spectral library using probabilistic artificial neural networks

Details Automated classification of ELODIE stellar spectral library using probabilistic artificial neural networks Automated classification of ELODIE stellar spectral library using probabilistic artificial neural networks

Mar 2008

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2008basi...36....1m&link_type=abstract

Bulletin of the Astronomical Society of India, Vol. 36, p. 1-54

Computer Science

Databases

1

Probabilistic Neural Network (Pnn), Stellar Spectra, Principal Component Analysis

Scientific paper

A Probabilistic Neural Network model has been used for automated classification of ELODIE stellar spectral library consisting of about 2000 spectra into 158 known spectro-luminosity classes. The full spectra with 561 flux bins and a PCA reduced set of 57, 26 and 16 components have been used for the training and test sessions. The results show a spectral type classification accuracy of 3.2 sub-spectral type and luminosity class accuracy of 2.7 for the full spectra and an accuracy of 3.1 and 2.6 respectively with the PCA set. This technique will be useful for future upcoming large databases and their rapid classification.

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