Density Estimation Based Model Matching Method for Redshift Determination
DUAN Fu-qing1, WU Fu-chao1, LUO A-li2, ZHAO Yong-heng2
1. National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, China 2. National Observatory of Beijing, Chinese Academy of Sciences, Beijing 100012, China
Abstract:The present paper proposes a model matching method based on density estimation for redshift determination, in which the problem of redshift determination is translated into the problem of searching for the point of maximum density within a data set. At first, the mean shift-based method for auto-extraction of spectral lines is used to get feature spectral lines. Secondly, according to the redshift formula, the authors use the feature wavelength array and the spectral template to get a data set. Finally, the authors find the point of maximum density within the data set, then the average of the data in ε-neighbor of the point is regarded as the redshift estimation. The information of feature wavelength and spectral line type is used in this method so that it can deal with every kind of spectra. Experiments show that our method is stable and the correct identification rate is high.
Key words:Spectral analysis;Redshift determination;Model matching;Feature spectral line
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