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Automated Classification of Sloan Digital Sky Survey (SDSS) Stellar Spectra using Artificial Neural Networks

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      Abstract

      Automated techniques have been developed to automate the process of classification of objects or their analysis. The large datasets provided by upcoming spectroscopic surveys with dedicated telescopes urges scientists to use these automated techniques for analysis of such large datasets which are now available to the community. Sloan Digital Sky Survey (SDSS) is one of such surveys releasing massive datasets. We use Probabilistic Neural Network (PNN) for automatic classification of about 5000 SDSS spectra into 158 spectral type of a reference library ranging from O type to M type stars.

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      Journal
      26 April 2008
      0804.4219
      10.1007/s10509-008-9816-5

      http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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      Astrophys.Space Sci.315:201-210,2008
      27 pages, 11 figures To appear in Astrophys. Space Sci., 2008
      astro-ph

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