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Volumn 11, Issue 7, 2004, Pages 597-600

Investigations of non-Gaussian factor Analysis

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTATIONAL COMPLEXITY; COMPUTER SIMULATION; CONVERGENCE OF NUMERICAL METHODS; INDEPENDENT COMPONENT ANALYSIS; INTEGRAL EQUATIONS; ITERATIVE METHODS; LEAST SQUARES APPROXIMATIONS; MATHEMATICAL MODELS; MONTE CARLO METHODS; OPTIMIZATION; PROBABILITY DENSITY FUNCTION;

EID: 3142756981     PISSN: 10709908     EISSN: None     Source Type: Journal    
DOI: 10.1109/LSP.2004.828928     Document Type: Article
Times cited : (4)

References (13)
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    • Byy harmony learning, independent state space and generalized APT financial analysis
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    • Xu, L.1
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    • EM algorithm for ML factor analysis
    • D. Rubi and D. Thayer, "EM algorithm for ML factor analysis," Psychometrika, vol. 57, pp. 69-76, 1976.
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    • Rubi, D.1    Thayer, D.2
  • 7
    • 0030676410 scopus 로고    scopus 로고
    • Maximum likelihood for blind separation and deconvolution of noisy signals using mixture models
    • E. Moulines, J. Cardoso, and E. Gassiat, "Maximum likelihood for blind separation and deconvolution of noisy signals using mixture models," in Proc. ICASSP'97, 1997, pp. 3617-3620.
    • (1997) Proc. ICASSP'97 , pp. 3617-3620
    • Moulines, E.1    Cardoso, J.2    Gassiat, E.3
  • 8
    • 0012671071 scopus 로고    scopus 로고
    • Bayesian Ying-Yang system and theory as a unified statistical learning approach (iii): Models and algorithms for dependence reduction, data dimension reduction, ICA and supervised learning
    • K. M. Wong et al., Ed. New York: Springer-Verlag
    • L. Xu, "Bayesian Ying-Yang system and theory as a unified statistical learning approach (iii): Models and algorithms for dependence reduction, data dimension reduction, ICA and supervised learning," in Theoretical Apsects of Neural Computation: A Multidisciplinary Perspective, K. M. Wong et al., Ed. New York: Springer-Verlag, 1997, vol. 43-60.
    • (1997) Theoretical Apsects of Neural Computation: A Multidisciplinary Perspective , vol.43 , pp. 60
    • Xu, L.1
  • 9
    • 0033561886 scopus 로고    scopus 로고
    • Independent factor analysis
    • H. Attias, "Independent factor analysis," Neural Computation, vol. 11, pp. 803-851, 1999.
    • (1999) Neural Computation , vol.11 , pp. 803-851
    • Attias, H.1
  • 10
    • 0035259214 scopus 로고    scopus 로고
    • Best harmony, unified RPCL and automated model selection for unsupervised and supervised learning on Gaussian mixtures, three-layer nets and ME-RBF-SVM models
    • L. Xu, "Best harmony, unified RPCL and automated model selection for unsupervised and supervised learning on Gaussian mixtures, three-layer nets and ME-RBF-SVM models," Int. J. Neural Syst., vol. 11, pp. 43-70, 2001.
    • (2001) Int. J. Neural Syst. , vol.11 , pp. 43-70
    • Xu, L.1
  • 12
    • 0002629270 scopus 로고
    • Maximum-likelihood from incomplete data via the EM algorithm
    • A. P. Dempster, N. M. Laird, and D. B. Rubin, "Maximum-likelihood from incomplete data via the EM algorithm," J. R. Statist. Soc. B, vol. 39, pp. 1-38, 1977.
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  • 13
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    • Asymptotic convergence rate of the EM algorithm for Gaussian mixtures
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    • (2000) Neural Comput. , vol.12 , Issue.12 , pp. 2881-2907
    • Ma, J.1    Xu, L.2    Jordan, M.I.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.