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Convergence of algorithms used for principal component analysis
Zhang, JH; Chen, HF
1997-12-01
Source PublicationSCIENCE IN CHINA SERIES E-TECHNOLOGICAL SCIENCES
ISSN1006-9321
Volume40Issue:6Pages:597-604
AbstractThe convergence of algorithms used for principal component analysis is analyzed. The algorithms are proved to converge to eigenvectors and eigenvalues of a matrix A which is the expectation of observed random samples. The conditions required here are considerably weaker than those used in previous work.
Keywordprincipal component analysis stochastic approximation algorithms convergence
Language英语
WOS Research AreaEngineering ; Materials Science
WOS SubjectEngineering, Multidisciplinary ; Materials Science, Multidisciplinary
WOS IDWOS:A1997YK88000006
PublisherSCIENCE CHINA PRESS
Citation statistics
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/28998
Collection中国科学院数学与系统科学研究院
AffiliationCHINESE ACAD SCI,INST SYST SCI,BEIJING 100080,PEOPLES R CHINA
Recommended Citation
GB/T 7714
Zhang, JH,Chen, HF. Convergence of algorithms used for principal component analysis[J]. SCIENCE IN CHINA SERIES E-TECHNOLOGICAL SCIENCES,1997,40(6):597-604.
APA Zhang, JH,&Chen, HF.(1997).Convergence of algorithms used for principal component analysis.SCIENCE IN CHINA SERIES E-TECHNOLOGICAL SCIENCES,40(6),597-604.
MLA Zhang, JH,et al."Convergence of algorithms used for principal component analysis".SCIENCE IN CHINA SERIES E-TECHNOLOGICAL SCIENCES 40.6(1997):597-604.
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