Bazarghan Mahdi*
Abstract.
A Probabilistic Neural Network model has been used for
auto-
mated 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.
Keywords: : Probabilistic Neural Network
(PNN) - stellar spectra - Principal
Component Analysis
Inter University Center for Astronomy & Astrophysics, Post Bag 4,
Ganeshkhind,
Pune 411 007, India