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An Automatic Detection and Classification Method of the Splicing Abnormality in the Stellar Spectra for LAMOST
Meng Fan-long1; Pan Jing-chang1; Yu Jing-jing1; Wei Peng2
2017-07-01
Source PublicationSPECTROSCOPY AND SPECTRAL ANALYSIS
Volume37Issue:7Pages:2250-2253
AbstractSplicing abnormality is a phenomenon of poor continuity spectrum showed in the splicing wavelengths of the red and blue end. In the spectral processing, this problem can be caused by several factors, such as stability of instrument, observation condition, the response function and so on. It has important effect on the spectra quality whether the splicing is normal or not. In the research of this paper we define a tag on the Lamost spectra automatically to evaluate the quality of spectra splicing and it can provide users with a choice when using data. In this paper, a method of automatic detection of splicing abnormality spectra for LAMOST is proposed to improve the work efficiency greatly. With this method, first of all, we get the red end and blue end of the test spectrum in the splicing wavelengths after flux normalized and the feature lines deleted. Then, we fit the continuum in the red and blue end separately. Thirdly, we calculate the differences of flux between the two fitted curves at a series of independent variables with regular intervals. We get the average and standard deviation of the differences and the area of the two curves busied. Based on the statistics above, an evaluation function is presented in this paper which can be used to judge whether the test spectra are normal or not and determine their abnormal class. The method has been proved to have a good effect in the reorganization of splicing abnormality spectra through a mass of experiments.
SubtypeArticle
KeywordSplicing Wavelengths Spectra Pretreatment Segmentation Fitting Deviation Abnormal Grading
WOS HeadingsScience & Technology ; Technology
DOI10.3964/j.issn.1000-0593(2017)07-2250-04
Indexed BySCI
Language英语
WOS Research AreaSpectroscopy
WOS SubjectSpectroscopy
WOS IDWOS:000405648400046
Citation statistics
Document Type期刊论文
Identifierhttp://ir.bao.ac.cn/handle/114a11/8865
Collection星系宇宙学研究部
Affiliation1.Shandong Univ Weihai, Sch Mech Elect & Informat Engn, Weihai 264209, Peoples R China
2.Chinese Acad Sci, Key Lab Opt Astron, Natl Astron Observ, Beijing 100012, Peoples R China
Recommended Citation
GB/T 7714
Meng Fan-long,Pan Jing-chang,Yu Jing-jing,et al. An Automatic Detection and Classification Method of the Splicing Abnormality in the Stellar Spectra for LAMOST[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS,2017,37(7):2250-2253.
APA Meng Fan-long,Pan Jing-chang,Yu Jing-jing,&Wei Peng.(2017).An Automatic Detection and Classification Method of the Splicing Abnormality in the Stellar Spectra for LAMOST.SPECTROSCOPY AND SPECTRAL ANALYSIS,37(7),2250-2253.
MLA Meng Fan-long,et al."An Automatic Detection and Classification Method of the Splicing Abnormality in the Stellar Spectra for LAMOST".SPECTROSCOPY AND SPECTRAL ANALYSIS 37.7(2017):2250-2253.
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