Spectral pattern recognition with regularized Gaussian classifier

In this paper we propose to adopt a regularized Gaussian classifier for spectral pattern recognition. To deal with ill-posed covariance matrix estimation problem in constructing the classifier, we develop a novel technique for fast estimation of regularization parameter. Experiments are conducted to investigate the real-world stellar spectra data recognition with the developed technique. Higher classification accuracy results are obtained and demonstrated.