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Volumn , Issue , 1999, Pages 508-514

Unsupervised classification with non-Gaussian mixture models using ICA

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMMUNICATION CHANNELS (INFORMATION THEORY); GAUSSIAN NOISE (ELECTRONIC); IMAGE SEGMENTATION;

EID: 84899004910     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (46)

References (15)
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    • Attias, H.1
  • 2
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    • An information-maximization approach to blind separation and blind deconvolution
    • Bell, A. J. and Sejnowski, T. J. (1995). An Information-Maximization Approach to Blind Separation and Blind Deconvolution. Neural Computation, 7:1129-1159.
    • (1995) Neural Computation , vol.7 , pp. 1129-1159
    • Bell, A.J.1    Sejnowski, T.J.2
  • 3
    • 0030832881 scopus 로고    scopus 로고
    • The 'independent components' of natural scenes are edge filters
    • Bell, A. J. and Sejnowski, T. J. (1997). The 'independent components' of natural scenes are edge filters. Vision Research, 37(23):3327-3338.
    • (1997) Vision Research , vol.37 , Issue.23 , pp. 3327-3338
    • Bell, A.J.1    Sejnowski, T.J.2
  • 5
    • 0000390697 scopus 로고    scopus 로고
    • Equivariant adaptive source separation
    • Cardoso, J.-F. and Laheld, B. (1996). Equivariant adaptive source separation. IEEE Trans, on S.P., 45(2):434-444.
    • (1996) IEEE Trans, on S.P. , vol.45 , Issue.2 , pp. 434-444
    • Cardoso, J.-F.1    Laheld, B.2
  • 8
    • 0000324990 scopus 로고    scopus 로고
    • An alternative perspective on adaptive independent component analysis algorithms
    • Girolami, M. (1998). An alternative perspective on adaptive independent component analysis algorithms. Neural Computation, 10(8):2103-2114.
    • (1998) Neural Computation , vol.10 , Issue.8 , pp. 2103-2114
    • Girolami, M.1
  • 10
    • 0033556834 scopus 로고    scopus 로고
    • Independent component analysis using an extended infomax algorithm for mixed sub-Gaussian and super-Gaussian sources
    • Lee, T.-W., Girolami, M., and Sejnowski, T. J. (1999b). Independent component analysis using an extended infomax algorithm for mixed sub-gaussian and super-gaussian sources. Neural Computation, 11(2):409-433.
    • (1999) Neural Computation , vol.11 , Issue.2 , pp. 409-433
    • Lee, T.-W.1    Girolami, M.2    Sejnowski, T.J.3
  • 11
    • 0011006550 scopus 로고    scopus 로고
    • ICA mixture models for unsupervised classification and automatic context switching
    • Aussois, in press
    • Lee, T.-W., Lewicki, M. S., and Sejnowski, T. J. (1999c). ICA mixture models for unsupervised classification and automatic context switching. In International Workshop on ICA, Aussois, in press.
    • (1999) International Workshop on ICA
    • Lee, T.-W.1    Lewicki, M.S.2    Sejnowski, T.J.3
  • 12
    • 0012523816 scopus 로고    scopus 로고
    • Inferring sparse, overcomplete image codes using an efficient coding framework
    • Lewicki, M. and Olshausen, B. (1998). Inferring sparse, overcomplete image codes using an efficient coding framework. In Advances in Neural Information Processing Systems 10, pages 556-562.
    • (1998) Advances in Neural Information Processing Systems , vol.10 , pp. 556-562
    • Lewicki, M.1    Olshausen, B.2
  • 14
    • 0029938380 scopus 로고    scopus 로고
    • Emergence of simple-cell receptive field properties by learning a sparse code for natural images
    • Olshausen, B. and Field, D. (1996). Emergence of simple-cell receptive field properties by learning a sparse code for natural images. Nature, 381:607-609.
    • (1996) Nature , vol.381 , pp. 607-609
    • Olshausen, B.1    Field, D.2
  • 15
    • 0003202407 scopus 로고
    • Autoclass - A Bayesian approach to classification
    • Kluwer Academic Publishers
    • Stutz, J. and Cheeseman, P. (1994). Autoclass - a Bayesian approach to classification. Maximum Entropy and Bayesian Methods, Kluwer Academic Publishers.
    • (1994) Maximum Entropy and Bayesian Methods
    • Stutz, J.1    Cheeseman, P.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.