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Red Shift Determination and Spectral Line Identification Based on Knowledge |
Liu Rong①; Duan Fu-qing②; Liu San-yang①;Wu Fu-chao② |
①Department of Mathematics, Xidian University, Xi’an 710071, China;②National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences. Beijing 100080, China |
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Abstract A novel method for redshift determination and spectral line identification of celestial spectra is presented, which is based on the knowledge of feature spectral lines. Firstly, definition of redshift candidate and feature spectral line candidate is given, and the candidates are cross-validated according to the definition; Secondly, the density is estimated at every redshift candidate by using the Parzen window technique; Finally, the average of redshift candidates in Parzen window of the redshift candidate with maximum density is the redshift, and the feature spectral line candidates corresponding to those redshift candidates are feature spectral lines. Compared with other methods of the same kind, this method has a lower dependence on the quality of spectral line extraction. Experiments show that this method is robust and the correct rate is encouraging.
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Received: 15 December 2004
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