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Instituto de Astronomía y Meteorología, Universidad de Guadalajara
Address:
Mexico
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Abstract Reference: 30341
Identifier: P1.10
Presentation: Poster presentation
Key Theme: 1 Reduction and Analysis Algorithms for Large Databases and Vice-versa

Effect of the signal to noise ratio on the accuracy of the automatic spectral classification of stellar spectra

Authors:
Corral Luis J., Navarro Silvana G., Villavicencio Edgar

The signal to noise ratio (S/N) is an important parameter that greatly affect the accuracy of the automatic spectral classification. We present  the analysis made over the automatic spectral classification of stellar spectra with different levels of S/N. We trained specialized neural networks with spectra at different S/N  levels in order to minimize such effect and present here the quantitative analysis of the accuracy in the spectral classification.