Abstract
An automatic spectral classification system has been developed for objective prism spectra (dispersion 830 and 2440 Å/mm at H γ) of LMC stars, taken with the 1.2m UK Schmidt Telescope in Australia. A supervised method based on artificial neural networks (ANNs) has been successfully used, and a comparison with visually-classified spectra is reported. Furthermore, an unsupervised neural network approach based on the Kohonen SOM method has been tested: spectra containing peculiarities can be evidenced, and the possibility of classifying automatically objective-prism spectra using minimal a-priori information is demonstrated.
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© 1997 Springer Science+Business Media Dordrecht
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Pasian, F., Smareglia, R., Hantzios, P., Dapergolas, A., Bellas-Velidis, I. (1997). Automated Objective Prism Spectral Classification Using Neural Networks. In: Kontizas, E., Kontizas, M., Morgan, D.H., Vettolani, G.P. (eds) Wide-Field Spectroscopy. Astrophysics and Space Science Library, vol 212. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-5722-3_14
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DOI: https://doi.org/10.1007/978-94-011-5722-3_14
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