Computer Science – Databases
Scientific paper
Jan 1999
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1999iaus..192..369g&link_type=abstract
The stellar content of Local Group galaxies, Proceedings of the 192nd symposium of the International Astronomical Union held in
Computer Science
Databases
1
Scientific paper
With the improvements in observational tools, it is feasible to have a larger databases of low resolution spectroscopy. In order to extract observational and physical properties from such databases, it is necessary to employ computer methods, such as artificial neural networks and principal component analysis. Our group is involved in investigating the potential of new tools to derive stellar classification and atmospheric parameters from low resolution spectroscopy (see e.g. Gulati et al., 1994, 426, 340; Gulati et al., 1997, 322, 933; Singh et al., 1998, MNRAS, 295, 312). I would like to present the current status of automating this process. We envisage the use of such methods for study of the stellar content of stellar systems whose stellar content can be resolved with the modern detectors.
Altamirano L. R.
Bravo Ana
Gulati Ravi K.
Padilla Gabriel
No associations
LandOfFree
The Application of Artificial Neural Networks: A Catalog of Spectral Indices 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 The Application of Artificial Neural Networks: A Catalog of Spectral Indices, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and The Application of Artificial Neural Networks: A Catalog of Spectral Indices will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-1610682