Next: Methods for Structuring and Searching Very Large Catalogs . ... We have explored two automated classification methods: supervised classification using Artificial Neural Networks (ANN) and unsupervised classification using Self Organized Maps (SOM). These methods are used to classify IUE low-dispersion spectra of normal stars with spectral types ranging from O3 to G5. This paper describes the application of automated methods to the problem of the classification of stellar spectra. ...

... Automated Spectral Classification Using Neural Networks E. F. Vieira Laboratorio de AstrofТРsica Espacial y FТРsica Fundamental P.O.Box 50727, 28080 Madrid, Spain, Email: efv@lae#.esa.es J. D. Ponz GSED/ESA, Villafranca P.O.Box 50727, 28080 Madrid, Spain, Email: jdp@vilspa.esa.es Abstract. We have explored two automated classification methods: supervised classification using Artificial Neural Networks (ANN) and unн supervised classification using Self Organized Maps (SOM). ...

IRAF/STECF 2-D spectrum point source / background decomposition package . ... The general problem is one of spectral decomposition - of separating the spectra of the point sources from the background. ... The STECF IRAF layered package "specres" provides two tasks to extract point source spectra from 2-D images (either longslit, multislit or cross-dispersed) and decompose the full background over the image. ... A Point Source Function spectrum image is required as a 2-D spectrum. ...