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Volumn 13, Issue 3, 2001, Pages 677-689

A constrained EM algorithm for independent component analysis

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; PHYSIOLOGY; VISUAL SYSTEM;

EID: 0035292754     PISSN: 08997667     EISSN: None     Source Type: Journal    
DOI: 10.1162/089976601300014510     Document Type: Article
Times cited : (39)

References (20)
  • 1
    • 33749754615 scopus 로고    scopus 로고
    • A new algorithm for blind signal separation
    • D. Touretzky, M. Mozer, and M. Hasselmo (Eds.). Cambridge, MA: MIT Press
    • Amari, S., Cichocki, A., & Yang, H. (1996). A new algorithm for blind signal separation. In D. Touretzky, M. Mozer, and M. Hasselmo (Eds.), Advances in neural information processing systems, 8 (pp. 757-763). Cambridge, MA: MIT Press.
    • (1996) Advances in Neural Information Processing Systems , vol.8 , pp. 757-763
    • Amari, S.1    Cichocki, A.2    Yang, H.3
  • 2
    • 0033561886 scopus 로고    scopus 로고
    • Independent factor analysis
    • Attias, H. (1999). Independent factor analysis. Neural Computation, 11, 803-851.
    • (1999) Neural Computation , vol.11 , pp. 803-851
    • Attias, H.1
  • 3
    • 0001471775 scopus 로고
    • Unsupervised learning
    • Barlow, H. (1989). Unsupervised learning. Neural Computation, 1, 295-311.
    • (1989) Neural Computation , vol.1 , pp. 295-311
    • Barlow, H.1
  • 4
    • 0029411030 scopus 로고
    • An information-maximization approach to blind separation and blind deconvolution
    • Bell, A., & Sejnowski, T. (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.1    Sejnowski, T.2
  • 5
    • 0030832881 scopus 로고    scopus 로고
    • The independent components of natural scenes are edge filters
    • Bell, A., & Sejnowski, T. (1997). The independent components of natural scenes are edge filters. Vision Research, 37, 3327-3338.
    • (1997) Vision Research , vol.37 , pp. 3327-3338
    • Bell, A.1    Sejnowski, T.2
  • 7
    • 0028416938 scopus 로고
    • Independent component analysis, a new concept?
    • Comon, P. (1994). Independent component analysis, a new concept? Signal Processing, 36, 287-314.
    • (1994) Signal Processing , vol.36 , pp. 287-314
    • Comon, P.1
  • 8
    • 0031455770 scopus 로고    scopus 로고
    • An extended exploratory projection pursuit network with linear and nonlinear anti-Hebbian lateral connections applied to the cocktail party problem
    • Girolami, M., & Fyfe, C. (1997). An extended exploratory projection pursuit network with linear and nonlinear anti-Hebbian lateral connections applied to the cocktail party problem. Neural Networks, 10, 1607-1618.
    • (1997) Neural Networks , vol.10 , pp. 1607-1618
    • Girolami, M.1    Fyfe, C.2
  • 9
    • 0003905751 scopus 로고    scopus 로고
    • Independent component analysis by minimization of mutual information
    • Helsinki University of Technology, Laboratory of Computer and Information Science
    • Hyvärinen, A. (1997). Independent component analysis by minimization of mutual information (Tech. Rep.). Helsinki University of Technology, Laboratory of Computer and Information Science.
    • (1997) Tech. Rep.
    • Hyvärinen, A.1
  • 10
    • 0026191274 scopus 로고
    • Blind separation of sources, part 1: An adaptive algorithm based on neuromimetic architecture
    • Jutten, C., & Hérault, J. (1991). Blind separation of sources, part 1: An adaptive algorithm based on neuromimetic architecture. Signal Processing, 2, 1-10.
    • (1991) Signal Processing , vol.2 , pp. 1-10
    • Jutten, C.1    Hérault, J.2
  • 11
    • 0033556834 scopus 로고    scopus 로고
    • Independent component analysis using an extended infomax algorithm for mixed sub-gaussian and supergaussian sources
    • Lee, T., Girolami, M., & Sejnowski, T. (1999). Independent component analysis using an extended infomax algorithm for mixed sub-gaussian and supergaussian sources. Neural Computation, 11, 409-433.
    • (1999) Neural Computation , vol.11 , pp. 409-433
    • Lee, T.1    Girolami, M.2    Sejnowski, T.3
  • 12
    • 0034133184 scopus 로고    scopus 로고
    • Learning overcomplete representations
    • Lewicki, M., & Sejnowski, T. (2000). Learning overcomplete representations. Neural Computation, 12, 337-366.
    • (2000) Neural Computation , vol.12 , pp. 337-366
    • Lewicki, M.1    Sejnowski, T.2
  • 13
  • 15
    • 0030676410 scopus 로고    scopus 로고
    • Maximum likelihood for blind separation and deconvolution of noisy signals using mixture models
    • Moulines, E., Cardoso, J., & Gassiat, E. (1997). Maximum likelihood for blind separation and deconvolution of noisy signals using mixture models. In Proc. ICASSP, 5, 3617-3620.
    • (1997) Proc. ICASSP , vol.5 , pp. 3617-3620
    • Moulines, E.1    Cardoso, J.2    Gassiat, E.3
  • 16
    • 0343416807 scopus 로고    scopus 로고
    • The nonlinear PCA learning rule in independent component analysis
    • Oja, E. (1997). The nonlinear PCA learning rule in independent component analysis. Neurocomputing, 17, 25-45.
    • (1997) Neurocomputing , vol.17 , pp. 25-45
    • Oja, E.1
  • 19
    • 0003520380 scopus 로고    scopus 로고
    • Probabilistic principal component analysis
    • Aston University, Department of Computer Science and Applied Mathematics, Neural Computing Research Group
    • Tipping, M., & Bishop, C. (1997). Probabilistic principal component analysis (Tech. Rep. No. NCRG/97/010). Aston University, Department of Computer Science and Applied Mathematics, Neural Computing Research Group.
    • (1997) Tech. Rep. No. Ncrg/97/010
    • Tipping, M.1    Bishop, C.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.