Celestial Spectra Classification Based on Support Vector Machine

Spectra clasification is essentially a pattern recognition problem, so using SVM (Support Vector Machine) to do spectral classification is feasible. In addition, the spectra of special objects can be found through the classification. In this paper, we applied the SVM method to spectra classification by Matlab simulation programs, and analyze the results of the experiments. Experimental results show the ideal classification effects.