CASIA OpenIR  > 09年以前成果
Automated recognition of quasars based on adaptive radial basis function neural networks
Zhao, MF; Luo, AL; Wu, FC; Hu, ZY
Source PublicationSPECTROSCOPY AND SPECTRAL ANALYSIS
2006-02-01
Volume26Issue:2Pages:377-381
SubtypeArticle
AbstractRecognizing 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.
KeywordGalaxy Quasar Principal Component Analysis(Pca) Radial Basis Function Neural Networks K-means Clustering Gradient Descent
WOS HeadingsScience & Technology ; Technology
WOS KeywordGALAXIES ; PCA
Indexed BySCI
Language英语
WOS Research AreaSpectroscopy
WOS SubjectSpectroscopy
WOS IDWOS:000235638800045
Citation statistics
Cited Times:5[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/9198
Collection09年以前成果
Affiliation1.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
Recommended Citation
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.
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