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Volumn 5, Issue , 2004, Pages

PCA-ICA neural network model for polsar images analysis

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTATIONAL COMPLEXITY; DATA REDUCTION; GAUSSIAN NOISE (ELECTRONIC); INTEGRAL EQUATIONS; MATHEMATICAL MODELS; MATRIX ALGEBRA; OPTIMIZATION; PARAMETER ESTIMATION; SIGNAL PROCESSING; SIGNAL TO NOISE RATIO; STATISTICAL METHODS;

EID: 4544304045     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (9)

References (13)
  • 2
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    • S. Chitroub, A. Houacine, and B. Sansal, "Statistical characterisation and modelling of SAR images", Signal Processing, Vol. 82, No. 1, pp. 69-92, February 2002.
    • (2002) Signal Processing , vol.82 , Issue.1 , pp. 69-92
    • Chitroub, S.1    Houacine, A.2    Sansal, B.3
  • 3
    • 0026895279 scopus 로고
    • Principal component transformation of multifrequency polarimetric SAR imagery
    • July
    • J. S. Lee and K. Hoppel, "Principal component transformation of multifrequency polarimetric SAR imagery", IEEE Transactions on Geoscience & Remote Sensing, vol. 30, no. 4, PP. 686-696, July 1994.
    • (1994) IEEE Transactions on Geoscience & Remote Sensing , vol.30 , Issue.4 , pp. 686-696
    • Lee, J.S.1    Hoppel, K.2
  • 4
    • 4544374555 scopus 로고    scopus 로고
    • A new PCA-based method for data compression and enhancement of multifrequency polarimetric SAR imagery
    • S. Chitroub, A. Houacine, and B. Sansal, "A New PCA-based method for data compression and enhancement of multi-frequency polarimetric SAR imagery", Intelligent Data Analysis, International Journal, Vol. 6, No. 2, 2002.
    • (2002) Intelligent Data Analysis, International Journal , vol.6 , Issue.2
    • Chitroub, S.1    Houacine, A.2    Sansal, B.3
  • 5
    • 0034207888 scopus 로고    scopus 로고
    • A unifying information-theoretic framework for independent component analysis
    • T. W. Lee, M. Girolami, A. J. Bell, and T. J. Sejnowski, "A Unifying information-theoretic framework for independent component analysis", Neural Networks, Vol. 39, pp. 1-21, 2000.
    • (2000) Neural Networks , vol.39 , pp. 1-21
    • Lee, T.W.1    Girolami, M.2    Bell, A.J.3    Sejnowski, T.J.4
  • 6
    • 4544240521 scopus 로고    scopus 로고
    • Neuronal principal component analysis for an optimal representation of multispectral images
    • S. Chitroub, A. Houacine, and B. Sansal, "Neuronal principal component analysis for an optimal representation of multispectral images", Intelligent Data Analysis, International Journal, Vol. 5, No. 5, pp. 385-403, 2001.
    • (2001) Intelligent Data Analysis, International Journal , vol.5 , Issue.5 , pp. 385-403
    • Chitroub, S.1    Houacine, A.2    Sansal, B.3
  • 7
    • 0032612381 scopus 로고    scopus 로고
    • High-order contrasts for independent component analysis
    • J. F. Cardoso, "High-order contrasts for independent component analysis", Neural Computation, Vol. 11 No. 1, pp. 157-192, 1999.
    • (1999) Neural Computation , vol.11 , Issue.1 , pp. 157-192
    • Cardoso, J.F.1
  • 8
    • 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, Vol. 7, pp. 113-127, 1994.
    • (1994) Neural Networks , vol.7 , pp. 113-127
    • Karhunen, J.1    Joutsensalo, J.2
  • 9
    • 0032629347 scopus 로고    scopus 로고
    • Fast and robust fixed-point algorithms for independent component analysis
    • May
    • A. Hyvärinen, "Fast and robust fixed-point algorithms for independent component analysis", IEEE Transactions on Neural Networks, Vol. 10, No. 3, pp. 626-634, May 1999.
    • (1999) IEEE Transactions on Neural Networks , vol.10 , Issue.3 , pp. 626-634
    • Hyvärinen, A.1
  • 10
    • 0033556834 scopus 로고    scopus 로고
    • Independent component analysis using an extended infomax algorithm for mixed subgaussian and supergaussian sources
    • T. W. Lee, M. Girolami, and T. J. Sejnowski, "Independent component analysis using an extended infomax algorithm for mixed subgaussian and supergaussian sources", Neural Computation, Vol. 11, pp. 417-441, 1999.
    • (1999) Neural Computation , vol.11 , pp. 417-441
    • Lee, T.W.1    Girolami, M.2    Sejnowski, T.J.3
  • 13
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    • Stability analysis of adaptive blind source separation
    • S. Amari, T. P. Chen, and A. Cichocki, "Stability analysis of adaptive blind source separation", Neural Networks, Vol. 10, No. 8, pp. 1345-1352, 1997.
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    • Amari, S.1    Chen, T.P.2    Cichocki, A.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.