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Volumn , Issue , 1997, Pages 480-486

One-unit learning rules for Independent Component Analysis

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; BLIND SOURCE SEPARATION;

EID: 84898952096     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (33)

References (14)
  • 1
    • 0029411030 scopus 로고
    • An information-maximization approach to blind separation and blind deconvohition
    • Bell, A. and Sejnowski, T. (1995). An information-maximization approach to blind separation and blind deconvohition. Neural Computation, 7:1129-1159.
    • (1995) Neural Computation , vol.7 , pp. 1129-1159
    • Bell, A.1    Sejnowski, T.2
  • 2
    • 0000173039 scopus 로고    scopus 로고
    • Edges are the independent components of natural scenes
    • Denver, Colorado.
    • Bell, A. and Sejnowski, T. J. (1996)- Edges are the independent components of natural scenes. In NIPS *96, Denver, Colorado.
    • (1996) NIPS * , vol.96
    • Bell, A.1    Sejnowski, T.J.2
  • 4
    • 0028416938 scopus 로고
    • Independent component analysis - Anew concept?
    • Comon, P. (1994). Independent component analysis - anew concept? Signal Processing, 36:287-314.
    • (1994) Signal Processing , vol.36 , pp. 287-314
    • Comon, P.1
  • 5
    • 0002308310 scopus 로고
    • Adaptive blind separation of independent sources: A deflation approach
    • Delfbsse, N. and Loubaton, P. (1995). Adaptive blind separation of independent sources: a deflation approach. Signal Processing, 45:59-83.
    • (1995) Signal Processing , vol.45 , pp. 59-83
    • Delfbsse, N.1    Loubaton, P.2
  • 6
    • 0002254167 scopus 로고
    • On minimum entropy deconvolution
    • Academic Press
    • Donoho, D. (1981). On minimum entropy deconvolution. In Applied Time Series Analysis II. Academic Press.
    • (1981) Applied Time Series Analysis , vol.2
    • Donoho, D.1
  • 7
    • 0347835995 scopus 로고    scopus 로고
    • Image feature extraction using independent component analysis
    • Espoo, Finland
    • Hurri, J., Hyvarinen, A., Karkunen. J., and Oja, E. (1996). Image feature extraction using independent component analysis. In Proc. NORSIG'96, Espoo, Finland.
    • (1996) Proc. NORSIG'96
    • Hurri, J.1    Hyvarinen, A.2    Karkunen, J.3    Oja, E.4
  • 8
    • 0030673274 scopus 로고    scopus 로고
    • A family of fixed-point algorithms for independent component analysis
    • Munich, Germany
    • Hyvarinen, A. (1997). A family of fixed-point algorithms for independent component analysis. In Proc. ICASSP'97, Munich, Germany.
    • (1997) Proc. ICASSP'97
    • Hyvarinen, A.1
  • 9
    • 84899021235 scopus 로고    scopus 로고
    • Independent component analysis by general non-linear hebbian-like learning rules
    • Laboratory of Computer and Information Science
    • Hyvarinen, A. and Oja, E. (1996a). Independent component analysis by general non-linear hebbian-like learning rules. Technical Report A41, Helsinki University of Technology, Laboratory of Computer and Information Science.
    • (1996) Technical Report A41, Helsinki University of Technology
    • Hyvarinen, A.1    Oja, E.2
  • 10
    • 84899023682 scopus 로고    scopus 로고
    • Simple neuron models for independent component analysis
    • Laboratory of Computer and Information Science
    • Hyvarinen, A. and Oja, E. (1996b). Simple neuron models for independent component analysis. Technical Report A37, Helsinki University of Technology, Laboratory of Computer and Information Science.
    • (1996) Technical Report A37, Helsinki University of Technology
    • Hyvarinen, A.1    Oja, E.2
  • 11
    • 0346307721 scopus 로고    scopus 로고
    • A fast fixed-point algorithm for independent component analysis
    • To appear
    • Hyvarinen, A, and Oja, E. (1997). A fast fixed-point algorithm for independent component analysis. Neural Computation. To appear.
    • (1997) Neural Computation
    • Hyvarinen, A.1    Oja, E.2
  • 12
    • 0026191274 scopus 로고
    • Blind separation of sources, part I: An adaptive algorithm based on neiirnmimetic architecture
    • Jntten, C. and Herault, J. (1991). Blind separation of sources, part I: An adaptive algorithm based on neiirnmimetic architecture. Signal Proeessmi;, 24:1-10.
    • (1991) Signal Proeessmi , vol.24 , pp. 1-10
    • Jntten, C.1    Herault, J.2
  • 14
    • 0039136599 scopus 로고
    • The nonlinear PCA learning rule and signal separation - Mathematical analysis
    • Laboratory of Computer and Information Science. Submitted to a journal
    • Oja, E. (1995). The nonlinear PCA learning rule and signal separation - mathematical analysis. Technical Report A 26, Helsinki University of Technology, Laboratory of Computer and Information Science. Submitted to a journal.
    • (1995) Technical Report A 26, Helsinki University of Technology
    • Oja, E.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.