An intelligent system for the spectral classification of stars - artificial neural networks vs. statistical clustering techniques

This paper presents an intelligent system for the classification of low-resolution optical spectra of the stars in the current standard MK system. We propose a comparative analysis of two techniques, artificial neural networks and statistical clustering algorithms, applied to the spectral classification of a sample of approximately 258 optical spectra from public catalogues. We do not only intend to analyze the efficiency of these two approaches in the automatic classification of spectra; our final objective is the integration of several techniques in a unique intelligent hybrid system. This system is capable of applying the most appropriate classification method to each spectrum, which widely extends the research in the field of automatic classification.