Spectroscopy and Spectral Analysis, Volume. 42, Issue 4, 1186(2022)

LAMOST Unknown Spectral Analysis Based on Influence Space and Data Field

Yu-qing YANG*, Jiang-hui CAI1; 2; *;, Hai-feng YANG1; *;, Xu-jun ZHAO1;, and Xiao-na YIN1;
Author Affiliations
  • 1. School of Computer Science and Technology, Taiyuan University of Science and Technology, Taiyuan 030024, China
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    Figures & Tables(11)
    A sample of test data
    The center and examples of the first type of low SNR spectrum
    The center and examples of the second type of low SNR spectrum
    The center and examples of the third type of low SNR spectrum
    The center and examples of the fourth type of low SNR spectrum
    The center and examples of the fifth type of low SNR spectrum
    The proportion of five types low SNR spectra and their distribution in the sky area
    Seeing distribution of low SNR spectra
    Magnitude distribution of low SNR spectra
    SNR distribution of low SNR spectra
    The statistics distribution of different types of low SNR spectra on SPID and FiberID
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    Yu-qing YANG, Jiang-hui CAI, Hai-feng YANG, Xu-jun ZHAO, Xiao-na YIN. LAMOST Unknown Spectral Analysis Based on Influence Space and Data Field[J]. Spectroscopy and Spectral Analysis, 2022, 42(4): 1186

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    Paper Information

    Category: Research Articles

    Received: Jul. 23, 2021

    Accepted: --

    Published Online: Jul. 25, 2023

    The Author Email: Yu-qing YANG (B20180012@stu.tyust.edu.cn)

    DOI:10.3964/j.issn.1000-0593(2022)04-1186-06

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