| 光谱学与光谱分析 |
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| Automated Classification of Celestial Spectra Based on Support Vector Machines |
| QIN Dong-mei1, HU Zhan-yi1, ZHAO Yong-heng2 |
1. National Pattern Recognition Laboratory of Automation Institute, Chinese Academy of Sciences，Beijing 100080，China
2. National Astronomical Observatories, Chinese Academy of Sciences，Beijing 100012，China |
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Abstract The main objective of an automatic recognition system of celestial objects via their spectra is to classify celestial spectra and estimate physical parameters automatically. This paper proposes a new automatic classification method based on support vector machines to separate non-active objects from active objects via their spectra. With low SNR and unknown red-shift value, it is difficult to extract true spectral lines, and as a result, active objects can not be determined by finding strong spectral lines and the spectral classification between non-active and active objects becomes difficult. The proposed method in this paper combines the principal component analysis with support vector machines, and can automatically recognize the spectra of active objects with unknown red-shift values from non-active objects. It finds its applicability in the automatic processing of voluminous observed data from large sky surveys in astronomy.
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Received: 2003-01-21
Accepted: 2003-06-20
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Corresponding Authors:
QIN Dong-mei
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| Cite this article: |
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QIN Dong-mei,HU Zhan-yi,ZHAO Yong-heng. Automated Classification of Celestial Spectra Based on Support Vector Machines [J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2004, 24(04): 507-511.
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| URL: |
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http://www.gpxygpfx.com/EN/Y2004/V24/I04/507 |
[1] Connolly A J, Szalay A S, Bershady M A et al. Astronomical Journal, 1995，110(3)：1071.
[2] Galaz Gaspar, Lapparent Valerie de. Astronomy and Astrophysics, 1998，332：459.
[3] Zaritsky D, Zabludoff A I, Jeffrey A W. Astronomical Journal, 1995，110：1602.
[4] CHEN Nian-yi, QIN Pei, CHEN Rui-liang et al(陈念贻，钦 佩，陈瑞亮等). Application of Pattern Recognition methods in Chemistry and Chemical Engineering(模式识别方法在化学化工中的应用). Beijing: Science Press(北京：科学出版社)，2000. 23.
[5] Huang L Y, Sun F M, Hu Z Y. Intern. Confer. of Pattern Recognition 2000, Barcelona, Spain, 2000, Ⅱ: 499.
[6] Qin D M, Hu Z Y, Zhao Y H. SPIE'2001, Wuhan, China, 2001，4554：268.
[7] BIAN Zhao-qi, ZHANG Xue-gong(边肇祺，张学工). Pattern Recognition(模式识别). Beijing: Tsinghua University Press(北京：清华大学出版社)，2000.
[8] SHI Zhong-zhi(史忠植). Knowledge Discovery(知识发现). Beijing: Tsinghua University Press(北京：清华大学出版社)，2002.
[9] Jacoby G H, Hunter D A, Christian C A. Astrophysical Journal Supplement Series, 1984，56：257.
[10] Kinney A L, Calzetti D, Bohlin R C et al. Astrophysical Journal, 1996, 467: 38.
[11] Pickles A J. Astrophysical Journal Supplement Series, 1985, 59: 33.
[12] Pickles A J. Publications of the Astronomical Society of the Pacific, 1998, 110: 863.
[13] Kent S M. Astrophysics and Space Science, 1994，217(1-2)：27. |
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