Automated recognition of quasars based on adaptive radial basis function neural networks
文献类型：期刊论文
| 作者 | Zhao, MF; Luo, AL; Wu, FC ; Hu, ZY
|
| 刊名 | SPECTROSCOPY AND SPECTRAL ANALYSIS
 |
| 出版日期 | 2006-02-01 |
| 卷号 | 26期号:2页码:377-381 |
| 关键词 | galaxy quasar principal component analysis(PCA) radial basis function neural networks K-means clustering gradient descent |
| 英文摘要 | Recognizing and certifying quasars through the research on spectra is an important method in the field of astronomy. This paper presents a novel adaptive method for the automated recognition of quasars based on the radial basis function neural networks (RBFN). The proposed method is composed of the following three parts: (1) The feature space is reduced by the PCA (the principal component analysis) on the normalized input spectra; (2) An adaptive RBFN is constructed and trained in this reduced space. At first, the K-means clustering is used for the initialization, then based on the sum of squares errors and a gradient descent optimization technique, the number of neurons in the hidden layer is adaptively increased to improve the recognition performance; (3) The quasar spectra recognition is effectively carried out by the above trained RBFN. The author's proposed adaptive RBFN is shown to be able to not only overcome the difficulty of selecting the number of neurons in hidden layer of the traditional RBFN algorithm, but also increase the stability and accuracy of recognition of quasars. Besides, the proposed method is particularly useful for automatic voluminous spectra processing produced from a large-scale sky survey project, such as our LAMOST, due to its efficiency. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Spectroscopy |
| 研究领域[WOS] | Spectroscopy |
| 关键词[WOS] | GALAXIES ; PCA |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000235638800045 |
| 公开日期 | 2015-12-24 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/9198]  |
| 专题 | 自动化研究所_09年以前成果 |
| 作者单位 | 1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100080, Peoples R China 2.Chinese Acad Sci, Natl Astron Observ, Beijing 100012, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhao, MF,Luo, AL,Wu, FC,et al. Automated recognition of quasars based on adaptive radial basis function neural networks[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS,2006,26(2):377-381. |
| APA | Zhao, MF,Luo, AL,Wu, FC,&Hu, ZY.(2006).Automated recognition of quasars based on adaptive radial basis function neural networks.SPECTROSCOPY AND SPECTRAL ANALYSIS,26(2),377-381. |
| MLA | Zhao, MF,et al."Automated recognition of quasars based on adaptive radial basis function neural networks".SPECTROSCOPY AND SPECTRAL ANALYSIS 26.2(2006):377-381. |
入库方式： OAI收割
来源：自动化研究所
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