Expert systems and artificial neural networks applied to stellar optical spectroscopy: a comparative analysis

This work presents a comparative study of two computational techniques - expert systems and artificial neural networks - applied to a specific field of astrophysics, the classification of the optical spectra of stars. We present a description of various expert systems and neural networks models, and the comparison of the results obtained by each technique individually and by a combination of both. We do not only intend to analyse the efficiency of these two approaches in the classification of stellar spectra; our final objective is the integration of several techniques in a unique hybrid system. This system will be capable of applying the most appropriate classification method to each spectrum, which widely opens the research in the field of automatic spectral classification.