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Volumn 1327, Issue , 1997, Pages 519-528

Prom neural principal components to neural independent components

Author keywords

[No Author keywords available]

Indexed keywords

BLIND SOURCE SEPARATION; FUNCTIONS; INDEPENDENT COMPONENT ANALYSIS; NEURAL NETWORKS;

EID: 84956705985     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: None     Document Type: Conference Paper
Times cited : (1)

References (48)
  • 2
    • 0024774330 scopus 로고
    • Neural networks and principal components analysis: Learning from examples without local minima
    • P. Baldi and K. Hornik, Neural networks and principal components analysis: learning from examples without local minima. Neural Networks 2, 1989, 52-58.
    • (1989) Neural Networks , vol.2 , pp. 52-58
    • Baldi, P.1    Hornik, K.2
  • 3
    • 0029411030 scopus 로고
    • An information-maximization approach to blind separation and blind deconvolution
    • A.J. Bell and T.J. Sejnowski. An information-maximization approach to blind separation and blind deconvolution. Neural Computation, 7:1129-1159, 1995.
    • (1995) Neural Computation , vol.7 , pp. 1129-1159
    • Bell, A.J.1    Sejnowski, T.J.2
  • 4
    • 0025642041 scopus 로고
    • Eigen-structure of the fourth-order cumulant tensor with application to the blind source separation problem
    • Albuquerque, NM, USA, April 3-6
    • J.-F. Cardoso. Eigen-structure of the fourth-order cumulant tensor with application to the blind source separation problem. In Proc. IEEE Int. Conf. on Acoustics, Speech, and Signal Processing, pages 2655-2658, Albuquerque, NM, USA, April 3-6, 1990.
    • (1990) Proc. IEEE Int. Conf. On Acoustics, Speech, and Signal Processing , pp. 2655-2658
    • Cardoso, J.-F.1
  • 5
    • 0001452888 scopus 로고
    • Iterative techniques for blind source separation using only fourth-order cumulants
    • J.-F. Cardoso. Iterative techniques for blind source separation using only fourth-order cumulants. In Proc. EUSIPCO, pages 739-742, 1992.
    • (1992) Proc. EUSIPCO , pp. 739-742
    • Cardoso, J.-F.1
  • 8
    • 0028498103 scopus 로고
    • Robust learning algorithm for blind separation of signals
    • A. Chicocki, R. Unbehauen, and E. Rummert, Robust learning algorithm for blind separation of signals. Electronics Letters 30, 1994, pp. 1386-1387.
    • (1994) Electronics Letters , vol.30 , pp. 1386-1387
    • Chicocki, A.1    Unbehauen, R.2    Rummert, E.3
  • 9
    • 0002672258 scopus 로고
    • Multi-layer neural networks with a local adaptive learning rule for blind separation of source signals
    • A. Chicocki, W. Kasprzak, and S. Amari, Multi-layer neural networks with a local adaptive learning rule for blind separation of source signals. In Proc. NOLTA '95, pages 61-65, 1995.
    • (1995) Proc. NOLTA '95 , pp. 61-65
    • Chicocki, A.1    Kasprzak, W.2    Amari, S.3
  • 10
    • 0342622608 scopus 로고    scopus 로고
    • Blind signal extraction using self-adaptive non-linear hebbian learning rule
    • A. Cichocki, S. I. Amari, and R. Thawonmas. Blind signal extraction using self-adaptive non-linear hebbian learning rule. In Proc. NOLTA '96, pages 377-380, 1996.
    • (1996) Proc. NOLTA '96 , pp. 377-380
    • Cichocki, A.1    Amari, S.I.2    Thawonmas, R.3
  • 11
    • 0028416938 scopus 로고
    • Independent component analysis - A new concept?
    • P. Comon. Independent component analysis - a new concept? Signal Processing, 36:287-314, 1994.
    • (1994) Signal Processing , vol.36 , pp. 287-314
    • Comon, P.1
  • 13
    • 0002308310 scopus 로고
    • Adaptive blind separation of independent sources: A deflation approach
    • N. Delfosse and P. Loubaton, Adaptive blind separation of independent sources: a deflation approach. Signal Processing 45, 1995, pp. 59-83.
    • (1995) Signal Processing , vol.45 , pp. 59-83
    • Delfosse, N.1    Loubaton, P.2
  • 17
    • 0026727495 scopus 로고
    • Convergence analysis of local feature extraction algorithms
    • K. Hornik and C. Kuan, Convergence analysis of local feature extraction algorithms. Neural Networks 5, pp. 229-240, 1991.
    • (1991) Neural Networks , vol.5 , pp. 229-240
    • Hornik, K.1    Kuan, C.2
  • 18
    • 0346307721 scopus 로고    scopus 로고
    • A fast fixed-point algorithm for independent component analysis
    • A. Hyvärinen and E. Oja. A fast fixed-point algorithm for independent component analysis. To appear in Neural Computation, 1997.
    • (1997) To Appear in Neural Computation
    • Hyvärinen, A.1    Oja, E.2
  • 20
    • 84900024248 scopus 로고    scopus 로고
    • A family of fixed-point algorithms for independent component analysis
    • Helsinki University of Technology, Laboratory of Computer and Information Science
    • A. Hyvärinen. A family of fixed-point algorithms for independent component analysis. Technical Report A40, Helsinki University of Technology, Laboratory of Computer and Information Science, 1996.
    • (1996) Technical Report , vol.A40
    • Hyvärinen, A.1
  • 21
    • 84899021235 scopus 로고    scopus 로고
    • Independent component analysis by general non-linear Hebbian-like learning rules
    • Helsinki University of Technol­ogy, Laboratory of Computer and Information Science
    • A. Hyvärinen and E. Oja. 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.
    • (1996) Technical Report , vol.A41
    • Hyvärinen, A.1    Oja, E.2
  • 22
    • 0029747427 scopus 로고    scopus 로고
    • A neuron that learns to separate one independent component from linear mixtures
    • Washington, D.C., June 3-6
    • A. Hyvärinen and E. Oja. A neuron that learns to separate one independent component from linear mixtures. In Proc. IEEE Int. Conf. on Neural Networks, pages 62-67, Washington, D.C., June 3-6 1996.
    • (1996) Proc. IEEE Int. Conf. On Neural Networks , pp. 62-67
    • Hyvärinen, A.1    Oja, E.2
  • 23
    • 84898952096 scopus 로고    scopus 로고
    • One-unit learning rules for independent component analysis
    • Denver, Colorado
    • A. Hyvärinen and E. Oja. One-unit learning rules for independent component analysis. In NIPS*96, Denver, Colorado, 1996.
    • (1996) NIPS*96
    • Hyvärinen, A.1    Oja, E.2
  • 24
    • 0030673274 scopus 로고    scopus 로고
    • A family of fixed-point algorithms for independent component analysis
    • Munich, Germany
    • A. Hyvärinen. A family of fixed-point algorithms for independent component analysis. Proc. ICASSP'97, Munich, Germany, 1997.
    • (1997) Proc. ICASSP'97
    • Hyvärinen, A.1
  • 25
    • 0001547599 scopus 로고
    • Independent component analysis (INCA) versus independent component analysis
    • (J. Lacoume et al, eds), Elsevier
    • C. Jutten and J. Herault, Independent component analysis (INCA) versus independent component analysis. Signal Processing IV: Theories and Applications. (J. Lacoume et al, eds), pp. 643-646, Elsevier, 1988.
    • (1988) Signal Processing IV: Theories and Applications , pp. 643-646
    • Jutten, C.1    Herault, J.2
  • 26
    • 0026191274 scopus 로고
    • Blind separation of sources, part I: An adaptive algorithm based on neuromimetic architecture
    • C. Jutten and J. Herault. Blind separation of sources, part I: An adaptive algorithm based on neuromimetic architecture. Signal Processing, 24:10, 1991.
    • (1991) Signal Processing , vol.24
    • Jutten, C.1    Herault, J.2
  • 27
    • 0026378252 scopus 로고
    • Tracking of sinusoidal frequencies by neural network learning algorithms
    • Toronto, Canada
    • J. Karhunen and J. Joutsensalo, Tracking of sinusoidal frequencies by neural network learning algorithms. Proc. ICASSP-91, Toronto, Canada, 1991.
    • (1991) Proc. ICASSP-91
    • Karhunen, J.1    Joutsensalo, J.2
  • 28
    • 0028272776 scopus 로고
    • Representation and separation of signals using nonlinear PCA type learning
    • J. Karhunen and J. Joutsensalo. Representation and separation of signals using nonlinear PCA type learning. Neural Networks, 7(1):113-127, 1994.
    • (1994) Neural Networks , vol.7 , Issue.1 , pp. 113-127
    • Karhunen, J.1    Joutsensalo, J.2
  • 29
    • 0029061996 scopus 로고
    • Generalizations of Principal Component Analysis, optimization problems, and neural networks
    • J. Karhunen and J. Joutsensalo, Generalizations of Principal Component Analysis, optimization problems, and neural networks. Neural Networks 8, pp. 549-562, 1995.
    • (1995) Neural Networks , vol.8 , pp. 549-562
    • Karhunen, J.1    Joutsensalo, J.2
  • 31
    • 0030681706 scopus 로고    scopus 로고
    • Applications of neural blind separation to signal and image processing
    • Munich, Germany
    • J. Karhunen, A. Hyvarinen, R. Vigario, J. Hurri, and E. Oja. Applications of neural blind separation to signal and image processing. Proc. ICASSP'97, Munich, Germany, 1997.
    • (1997) Proc. ICASSP'97
    • Karhunen, J.1    Hyvarinen, A.2    Vigario, R.3    Hurri, J.4    Oja, E.5
  • 33
    • 0025623681 scopus 로고
    • A neural network learning algorithm for adaptive principal component extraction (APEX)
    • Albuquerque, NM
    • S. Kung and K. Diamantras, A neural network learning algorithm for adaptive principal component extraction (APEX). Proc. ICASSP-90, Albuquerque, NM, 1990, 861-864.
    • (1990) Proc. ICASSP-90 , pp. 861-864
    • Kung, S.1    Diamantras, K.2
  • 34
    • 0023981750 scopus 로고
    • Self-organization in a perceptual network
    • R. Linsker, Self-organization in a perceptual network. Computer, 1988, 105-117.
    • (1988) Computer , pp. 105-117
    • Linsker, R.1
  • 35
    • 0020464111 scopus 로고
    • A simplified neuron model as a principal components analyzer
    • E. Oja, A simplified neuron model as a principal components analyzer. J. Math. Biol. 15, 1982, 267-273.
    • (1982) J. Math. Biol , vol.15 , pp. 267-273
    • Oja, E.1
  • 37
    • 0022013023 scopus 로고
    • On stochastic approximation of the eigenvectors and eigenvalues of the expectation of a random matrix
    • E. Oja and J. Karhunen, On stochastic approximation of the eigenvectors and eigenvalues of the expectation of a random matrix. J. Math. Anal. Appl. 106, 1985, 69-84.
    • (1985) J. Math. Anal. Appl , vol.106 , pp. 69-84
    • Oja, E.1    Karhunen, J.2
  • 38
    • 0002399288 scopus 로고
    • Neural networks, principal components, and subspaces
    • E. Oja, Neural networks, principal components, and subspaces. Int. J. Neural Systems 1, 1989, 61-68.
    • (1989) Int. J. Neural Systems , vol.1 , pp. 61-68
    • Oja, E.1
  • 39
    • 0003168213 scopus 로고
    • Learning in nonlinear constrained Hebbian networks
    • Helsinki, Finland
    • E. Oja, H. Ogawa, and J. Wangviwattana, Learning in nonlinear constrained Hebbian networks. Proc. ICANN-91, Helsinki, Finland, 1991.
    • (1991) Proc. ICANN-91
    • Oja, E.1    Ogawa, H.2    Wangviwattana, J.3
  • 40
    • 0026954958 scopus 로고
    • Principal components, minor components, and linear neural networks
    • E. Oja. Principal components, minor components, and linear neural networks. Neural Networks, 5:927-935, 1992.
    • (1992) Neural Networks , vol.5 , pp. 927-935
    • Oja, E.1
  • 41
    • 84956607008 scopus 로고    scopus 로고
    • The nonlinear PCA learning rule and signal separation - Mathematical analysis
    • E. Oja. The nonlinear PCA learning rule and signal separation - mathematical analysis. To appear in Neurocomputing, 1997.
    • (1997) To Appear in Neurocomputing
    • Oja, E.1
  • 42
    • 0005001064 scopus 로고
    • Signal separation by nonlinear hebbian learning
    • M. Palaniswami, Y. Attikiouzel, R. Marks, D. Fogel, and T. Fukuda, editors, IEEE Press, New York
    • E. Oja and J. Karhunen. Signal separation by nonlinear hebbian learning. In M. Palaniswami, Y. Attikiouzel, R. Marks, D. Fogel, and T. Fukuda, editors, Computational Intelligence - a Dynamic System Perspective, pages 83-97. IEEE Press, New York, 1995.
    • (1995) Computational Intelligence - A Dynamic System Perspective , pp. 83-97
    • Oja, E.1    Karhunen, J.2
  • 43
    • 0030131079 scopus 로고    scopus 로고
    • Robust fitting by nonlinear neural units
    • E. Oja and L. Wang, Robust fitting by nonlinear neural units. Neural Networks 9, pp. 435-444, 1996.
    • (1996) Neural Networks , vol.9 , pp. 435-444
    • Oja, E.1    Wang, L.2
  • 45
    • 84956074083 scopus 로고
    • A self-organizing network for principal components analysis
    • J. Rubner and P. Tavan, A self-organizing network for principal components analysis. Europhys. Lett. 10, 1989, 693-689.
    • (1989) Europhys. Lett , vol.10 , pp. 689-693
    • Rubner, J.1    Tavan, P.2
  • 46
    • 0024883243 scopus 로고
    • Optimal unsupervised learning in a single-layer linear feedforward network
    • T.D. Sanger, Optimal unsupervised learning in a single-layer linear feedforward network. Neural Networks 2, 1989, 459-473.
    • (1989) Neural Networks , vol.2 , pp. 459-473
    • Sanger, T.D.1
  • 47
    • 0013309452 scopus 로고
    • Feature discovery through error-correcting learning
    • UCSD, Institute of Cognitive Science
    • R. Williams, Feature discovery through error-correcting learning. Tech. Rep. 8501, UCSD, Institute of Cognitive Science, 1985.
    • (1985) Tech. Rep , vol.8501
    • Williams, R.1
  • 48
    • 0026745682 scopus 로고
    • Modified Hebbian learning for curve and surface fitting
    • L. Xu, E. Oja and C. Suen, Modified Hebbian learning for curve and surface fitting. Neural Networks 5, pp. 441-457, 1992.
    • (1992) Neural Networks , vol.5 , pp. 441-457
    • Xu, L.1    Oja, E.2    Suen, C.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.