| 光谱学与光谱分析 |
|
|
|
|
|
| Using Neural Networks Based Template Matching Method to Obtain Redshifts of Normal Galaxies |
| XU Xin1，2，LUO A-li2，WU Fu-chao1，ZHAO Yong-heng2 |
1. National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, China
2. National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012, China |
|
|
|
|
Abstract Galaxies can be divided into two classes: normal galaxy (NG) and active galaxy (AG). In order to determine NG redshifts, an automatic effective method is proposed in this paper, which consists of the following three main steps: (1) From the template of normal galaxy, the two sets of samples are simulated, one with the redshift of 0.0-0.3, the other of 0.3-0.5, then the PCA is used to extract the main components, and train samples are projected to the main component subspace to obtain characteristic spectra. (2) The characteristic spectra are used to train a Probabilistic Neural Network to obtain a Bayes classifier. (3) An unknown real NG spectrum is first inputted to this Bayes classifier to determine the possible range of redshift, then the template matching is invoked to locate the redshift value within the estimated range. Compared with the traditional template matching technique with an unconstrained range, our proposed method not only halves the computational load, but also increases the estimation accuracy. As a result, the proposed method is particularly useful for automatic spectrum processing produced from a large-scale sky survey project.
|
|
Received: 2003-12-26
Accepted: 2004-05-18
|
|
|
|
Corresponding Authors:
XU Xin
|
|
| Cite this article: |
|
XU Xin,LUO A-li,WU Fu-chao, et al. Using Neural Networks Based Template Matching Method to Obtain Redshifts of Normal Galaxies[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2005, 25(06): 996-1001.
|
|
|
|
| URL: |
|
https://www.gpxygpfx.com/EN/Y2005/V25/I06/996 |
[1] John Tonry, Marc Davis. Astronomical Journal, 1979, 84: 1511.
[2] Karl Glazebrook，Alison R Offer, Kathryn Deeley. Astronomical Journal, 1998，492：98.
[3] QIU Bo, HU Zhan-yi, ZHAO Yong-heng(邱 波，胡占义，赵永恒). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2002，22(4)，695.
[4] LUO A-li(罗阿理). Methods in Automatic Technique for Astronomical Spectral Analysis(光谱自动分析技术中的模式识别方法研究). Doctor's Degree Dissertation(博士学位论文). National Astronomical Observatories, Chinese Academy of Sciences(中国科学院国家天文台)，2001.
[5] Anne L Kinney, Daniela Calzetti，et al. Astrophysical Journal, 1996, 467: 38.
[6] 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)，1999. 212.
[7] Storrie-Lombardi M C, Irwin M J, Hippel T von，et al. Vistas in Astronomy, 1994, 38(3): 331.
[8] Coryn A L Bailer-Jones, Mike Irwin, Hippel Ted von. Monthly Notices of the Royal Astronomical Society, 1998, 298(2): 361.
[9] Connolly A J, Szalay A S. Astronomical Journal, 1995, 110(3): 1071.
[10] Simon Folkes, Shai Ronen，et al. Monthly Notices of the Royal Astronomical Society, 1999, 308(2): 459.
[11] Darren S Madgwick, Alison L Coil，et al. Astrophysical Journal, 2003, 599(2): 997.
[12] YAN Ping-fan, ZHANG Chang-shui(阎平凡，张长水). Artificial Neural Networks and Evolutionary Computation(人工神经网络与模拟进化计算). Beijing: Tsinghua University Press(北京：清华大学出版社)，2000.
[13] Hippel T von, Storrie-Lombardi L J, Storrie-Lonbardi M C，et al. Monthly Notices of the Royal Astronomical Society, 1994, 269: 97.
[14] Mahonen P H, Hakala P J. Astrophysical Journal Letters, 1995, 452: L77.
[15] Daya M Rawson, Jeremy Bailey, Paul J Francis. Publications Astronomical Society of Australia, 1996, 13: 207.
[16] Folkes S R, Lahav O, Maddox S J. Monthly Notices of the Royal Astronomical Society, 1996, 283: 651.
[17] Andrew E Firth, Ofer Lahav, Rachel S Somerville. Monthly Notices of the Royal Astronomical Society, 2003, 339: 1195.
[18] Tagliaferri R, Longo G，et al. Astronomy and Astrophysics, 2003, 16: 297.
[19] Donald F Specht. Probabilistic Neural Networks for Classification, Mapping, or Associative Memory, In Proceedings IEEE Second International Conference on Neural Networks (San Diego, CA), 1988, 1: 525.
[20] Michael R Berthold, Jay Diamond. Neurocomputing, 1998, 19: 167.
[21] HU Guang-shu(胡广书). Digital Signal Processing(数字信号处理). Beijing: Tsinghua University Press(北京：清华大学出版社)，1997. 5.
[22] XU Dong, WU Zheng(许 东，吴 铮). System Analysis and Design Based on MATLAB6.x (基于MATLAB6.x的系统分析与设计). Xi'an: Xi'an Electronic Science and Technology University Press(西安：西安电子科技大学出版社), 2002.
[23] HUANG Ling-yun, HU Zhan-yi(黄凌云，胡占义). Spectroscopy and Spectral Analysis(光谱学与光谱分析)，2003，23(1)：187.
|
| [1] |
JIANG Bin, LIU Shu-hui, WANG Wen-yu, GAO Jun*. Research on Automatic Parameter Measurement of WDMS Spectra[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2017, 37(09): 2914-2918. |
| [2] |
YU Jing-jing1, PANG Jing-chang1*, MENG Fan-long1, WEI Peng2. The Automatic Detection of the Continuum Problem in the Stellar Spectra Based on Distance Metric[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2017, 37(07): 2246-2249. |
| [3] |
WANG Wen-yu1, 2, WANG Xin-jun2*, PAN Jing-chang1 . Searching for Dwarf Nova Candidates with Automatic Methods in Massive Spectra [J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2013, 33(12): 3411-3414. |
| [4] |
GAO Wei-wei1, SHEN Jian-xin1, WANG Yu-liang1, LIANG Chun1, ZUO Jing2 . Algorithm of Locally Adaptive Region Growing Based on Multi-Template Matching Applied to Automated Detection of Hemorrhages [J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2013, 33(02): 448-453. |
| [5] |
LIU Jie1, PAN Jing-chang1*, LIU Meng1, WEI Peng2, LUO A-li2 . Comparison of Different Template Matching Methods of Automatic Stellar Spectrum Parameter Measurement[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2013, 33(02): 558-561. |
| [6] |
LIU Jie1, PAN Jing-chang1*, WEI Peng2, LIU Meng1, LUO A-li2 . Automatic Stellar Spectrum Parameter Measurement Based on Similarity Measure [J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2012, 32(12): 3402-3405. |
| [7] |
LI Xiang-ru1, FENG Chun-ming2, WANG Yong-jun1, LU Yu1 . A Novel Spectrum Feature Extraction Method [J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2011, 31(10): 2856-2860. |
| [8] |
LI Xiang-ru1, LU Yu1, ZHOU Jian-ming2, WANG Yong-jun1 . Galaxy/Quasar Classification Based on Nearest Neighbor Method[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2011, 31(09): 2582-2585. |
| [9] |
JIANG Bin1,2, LUO A-li1, ZHAO Yong-heng1 . Data Mining of Cataclysmic Variables Candidates in Massive Spectra[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2011, 31(08): 2278-2282. |
| [10] |
LI Qing-bo1, LI Xiang1, ZHANG Guang-jun1*, XU Yi-zhuang2, WU Jin-guang2, SUN Xue-jun3 . Application of Probabilistic Neural Networks Method to Gastric Endoscope Samples Diagnosis Based on FTIR Spectroscopy [J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2009, 29(06): 1553-1557. |
| [11] |
XING Fei,GUO Ping*. Stellar Spectral Recognition Based on Wavelet De-Noising and SVM[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2006, 26(07): 1368-1372. |
| [12] |
LIU Rong1,LIU San-yang1,ZHAO Rui-zhen2 . An Auto-Extraction Method of Spectral Line for Normal Galaxy Spectra [J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2006, 26(03): 583-586. |
| [13] |
ZHAO Mei-fang1, LUO A-li2, WU Fu-chao1, HU Zhan-yi1 . Automated Recognition of Quasars Based on Adaptive Radial Basis Function Neural Networks[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2006, 26(02): 377-381. |
| [14] |
XU Xin1,2, WU Fu-chao1, HU Zhan-yi1, LUO A-li2 . A Novel Method for the Determination of Redshifts of Normal Galaxies by Non-Linear Dimensionality Reduction [J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2006, 26(01): 182-186. |
| [15] |
DUAN Fu-qing1, WU Fu-chao1, LUO A-li2, ZHAO Yong-heng2 . Density Estimation Based Model Matching Method for Redshift Determination[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2005, 25(11): 1895-1898. |
|
|
|
|
