Abstract

Massive spectroscopic surveys require automated methods of analysis. We present a technique which employs probabilistic neural network for classification of stellar spectra. We work with a set of stellar spectra prepared with the Sloan Digital Sky Surveys (SDSS) SEGUE-2, which consists of 10000 spectra with the wavelength range of 4502 to 6154 Å.