메뉴 건너뛰기




Volumn 14, Issue 3, 2003, Pages 534-543

Algorithms for nonnegative independent component analysis

Author keywords

Geodesic; Independent component analysis (ICA); Nonnegativity; Stiefel manifold

Indexed keywords

ACOUSTIC SIGNAL PROCESSING; ALGORITHMS; COMPUTER SIMULATION; CONSTRAINT THEORY; CONVERGENCE OF NUMERICAL METHODS; IMAGE SEGMENTATION; INDEPENDENT COMPONENT ANALYSIS; MATRIX ALGEBRA; PRINCIPAL COMPONENT ANALYSIS; PROBABILITY DENSITY FUNCTION; VECTORS;

EID: 0038460232     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNN.2003.810616     Document Type: Article
Times cited : (197)

References (36)
  • 1
    • 0028416938 scopus 로고
    • Independent component analysis-a new concept?
    • P. Comon, "Independent component analysis-a new concept?," Signal Processing, vol. 36, no. 3, pp. 287-314, 1994.
    • (1994) Signal Processing , vol.36 , Issue.3 , pp. 287-314
    • Comon, P.1
  • 3
    • 0033592606 scopus 로고    scopus 로고
    • Learning the parts of objects by nonnegative matrix factorization
    • Oct.
    • D. D. Lee and H. S. Seung, "Learning the parts of objects by nonnegative matrix factorization," Nature, vol. 401, pp. 788-791, Oct. 1999.
    • (1999) Nature , vol.401 , pp. 788-791
    • Lee, D.D.1    Seung, H.S.2
  • 4
    • 0028561099 scopus 로고
    • Positive matrix factorization: A nonnegative factor model with optimal utilization of error estimates of data values
    • P. Paatero and U. Tapper, "Positive matrix factorization: A nonnegative factor model with optimal utilization of error estimates of data values," Environmetrics, vol. 5, pp. 111-126, 1994.
    • (1994) Environmetrics , vol.5 , pp. 111-126
    • Paatero, P.1    Tapper, U.2
  • 5
    • 0034854666 scopus 로고    scopus 로고
    • Use of nonnegative matrix factorization for language model adaptation in a lecture transcription task
    • Salt Lake City, UT, May 7-11
    • M. Novak and R. Mammone, "Use of nonnegative matrix factorization for language model adaptation in a lecture transcription task," in Proc. 2001 IEEE Int. Conf. Acoust., Speech., Signal Processing, vol. 1, Salt Lake City, UT, May 7-11, 2001, pp. 541-544.
    • (2001) Proc. 2001 IEEE Int. Conf. Acoust., Speech., Signal Processing , vol.1 , pp. 541-544
    • Novak, M.1    Mammone, R.2
  • 7
    • 0037721406 scopus 로고    scopus 로고
    • Application of nonnegative matrix factorization to dynamic positron emission tomography
    • T.-W. Lee, T.-P. Jung, S. Makeig, and T. J. Sejnowski, Eds., San Diego, CA, Dec. 9-13
    • J. S. Lee, D. D. Lee, S. Choi, and D. S. Lee, "Application of nonnegative matrix factorization to dynamic positron emission tomography," in Proc. Int. Conf. Independent Component Anal. Signal Separation, T.-W. Lee, T.-P. Jung, S. Makeig, and T. J. Sejnowski, Eds., San Diego, CA, Dec. 9-13, 2001, pp. 629-632.
    • (2001) Proc. Int. Conf. Independent Component Anal. Signal Separation , pp. 629-632
    • Lee, J.S.1    Lee, D.D.2    Choi, S.3    Lee, D.S.4
  • 8
    • 0027206958 scopus 로고
    • Least mean square error reconstruction principle for self-organizing neural-nets
    • L. Xu, "Least mean square error reconstruction principle for self-organizing neural-nets," Neural Networks, vol. 6, no. 5, pp. 627-648, 1993.
    • (1993) Neural Networks , vol.6 , Issue.5 , pp. 627-648
    • Xu, L.1
  • 9
    • 0000852458 scopus 로고    scopus 로고
    • Development of low entropy coding in a recurrent network
    • G. F. Harpur and R. W. Prager, "Development of low entropy coding in a recurrent network," Network: Computation in Neural Systems, vol. 7, pp. 277-284, 1996.
    • (1996) Network: Computation in Neural Systems , vol.7 , pp. 277-284
    • Harpur, G.F.1    Prager, R.W.2
  • 10
    • 0005819124 scopus 로고    scopus 로고
    • Modeling multiple-cause structure using rectification constraints
    • D. Charles and C. Fyfe, "Modeling multiple-cause structure using rectification constraints," Network: Computation in Neural Systems, vol. 9, pp. 167-182, 1998.
    • (1998) Network: Computation in Neural Systems , vol.9 , pp. 167-182
    • Charles, D.1    Fyfe, C.2
  • 11
    • 0003684836 scopus 로고    scopus 로고
    • Low entropy coding with unsupervised neural networks
    • Ph.D. dissertation, Dept. Eng., Univ. Cambridge, Cambridge, U.K.
    • G. F. Harpur, "Low Entropy Coding with Unsupervised Neural Networks," Ph.D. dissertation, Dept. Eng., Univ. Cambridge, Cambridge, U.K., 1997.
    • (1997)
    • Harpur, G.F.1
  • 12
    • 0037185563 scopus 로고    scopus 로고
    • Understanding and controlling rotations in factor analytic models
    • P. Paatero, P. K. Hopke, X.-H. Song, and Z. Ramadan, "Understanding and controlling rotations in factor analytic models," Chemometrics Intell. Lab. Syst., vol. 60, no. 1-2, pp. 253-264, 2002.
    • (2002) Chemometrics Intell. Lab. Syst. , vol.60 , Issue.1-2 , pp. 253-264
    • Paatero, P.1    Hopke, P.K.2    Song, X.-H.3    Ramadan, Z.4
  • 13
    • 0036284161 scopus 로고    scopus 로고
    • A multi-layer sparse coding network learns contour coding from natural images
    • P. O. Hoyer and A. Hyvärinen, "A multi-layer sparse coding network learns contour coding from natural images," Vis. Res., vol. 42, no. 12, pp. 1593-1605, 2002.
    • (2002) Vis. Res. , vol.42 , Issue.12 , pp. 1593-1605
    • Hoyer, P.O.1    Hyvärinen, A.2
  • 14
    • 0009819092 scopus 로고    scopus 로고
    • Adaptive lateral inhibition for nonnegative ICA
    • T.-W. Lee, T.-P. Jung, S. Makeig, and T. J. Sejnowski, Eds., San Diego, CA, Dec. 9-13
    • M. D. Plumbley, "Adaptive lateral inhibition for nonnegative ICA," in Proc. Int. Conf. Independent Component Anal. Signal Separation, T.-W. Lee, T.-P. Jung, S. Makeig, and T. J. Sejnowski, Eds., San Diego, CA, Dec. 9-13, 2001, pp. 516-521.
    • (2001) Proc. Int. Conf. Independent Component Anal. Signal Separation , pp. 516-521
    • Plumbley, M.D.1
  • 15
    • 0036612776 scopus 로고    scopus 로고
    • Conditions for nonnegative independent component analysis
    • June
    • M. D. Plumbley, "Conditions for nonnegative independent component analysis," IEEE Signal Processing Lett., vol. 9, pp. 177-180, June 2002.
    • (2002) IEEE Signal Processing Lett. , vol.9 , pp. 177-180
    • Plumbley, M.D.1
  • 17
    • 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. Applicat., vol. 106, pp. 69-84, 1985.
    • (1985) J. Math. Anal. Applicat. , vol.106 , pp. 69-84
    • Oja, E.1    Karhunen, J.2
  • 18
    • 0026954958 scopus 로고
    • Principal components, minor components and linear neural networks
    • E. Oja, "Principal components, minor components and linear neural networks," Neural Networks, vol. 5, pp. 927-935, 1992.
    • (1992) Neural Networks , vol.5 , pp. 927-935
    • Oja, E.1
  • 19
    • 0038397430 scopus 로고
    • Feature discovery through error-correction learning
    • Inst. Cognitive Sci., Univ. California, San Diego, ICS Rep. 8501
    • R. J. Williams, "Feature Discovery Through Error-Correction Learning," Inst. Cognitive Sci., Univ. California, San Diego, ICS Rep. 8501. 1985.
    • (1985)
    • Williams, R.J.1
  • 20
    • 0343416807 scopus 로고    scopus 로고
    • The nonlinear PCA learning rule in independent component analysis
    • E. Oja, "The nonlinear PCA learning rule in independent component analysis," Neurocomputing, vol. 17, no. 1, pp. 25-45, 1997.
    • (1997) Neurocomputing , vol.17 , Issue.1 , pp. 25-45
    • Oja, E.1
  • 21
    • 0038059021 scopus 로고    scopus 로고
    • A 'nonnegative PCA' algorithm for independent component analysis
    • submitted for publication
    • M. D. Plumbley and E. Oja, A 'nonnegative PCA' algorithm for independent component analysis, 2002, submitted for publication.
    • (2002)
    • Plumbley, M.D.1    Oja, E.2
  • 22
    • 0033320487 scopus 로고    scopus 로고
    • Mechanical' neural learning for blind source separation
    • October
    • S. Fiori, "'Mechanical' neural learning for blind source separation," Electron. Lett., vol. 35, no. 22, pp. 1963-1964, October 1999.
    • (1999) Electron. Lett. , vol.35 , Issue.22 , pp. 1963-1964
    • Fiori, S.1
  • 25
    • 0000317856 scopus 로고    scopus 로고
    • Self-stabilized gradient algorithms for blind source separation with orthogonality constraints
    • Nov.
    • S. C. Douglas, "Self-stabilized gradient algorithms for blind source separation with orthogonality constraints," IEEE Trans. Neural Networks, vol. 11, pp. 1490-1497, Nov. 2000.
    • (2000) IEEE Trans. Neural Networks , vol.11 , pp. 1490-1497
    • Douglas, S.C.1
  • 26
    • 0033315772 scopus 로고    scopus 로고
    • Learning algorithm for ICA by geodesic flows on orthogonal group
    • Washington, DC, July 10-16
    • Y. Nishimori, "Learning algorithm for ICA by geodesic flows on orthogonal group," in Proc. Int. Joint Conf. Neural Networks, vol. 2, Washington, DC, July 10-16, 1999, pp. 933-938.
    • (1999) Proc. Int. Joint Conf. Neural Networks , vol.2 , pp. 933-938
    • Nishimori, Y.1
  • 27
    • 0032216898 scopus 로고    scopus 로고
    • The geometry of algorithms with orthogonality constraints
    • A. Edelman, T. A. Arias, and S. T. Smith, "The geometry of algorithms with orthogonality constraints," SIAM J. Matrix Anal. Applicat., vol. 20, no. 2, pp. 303-353, 1998.
    • (1998) SIAM J. Matrix Anal. Applicat. , vol.20 , Issue.2 , pp. 303-353
    • Edelman, A.1    Arias, T.A.2    Smith, S.T.3
  • 28
    • 0001586142 scopus 로고    scopus 로고
    • A theory for learning by weight flow on Stiefel-Grassman manifold
    • S. Fiori, "A theory for learning by weight flow on Stiefel-Grassman manifold," Neural Comput., vol. 13, pp. 1625-1647, 2001.
    • (2001) Neural Comput. , vol.13 , pp. 1625-1647
    • Fiori, S.1
  • 30
    • 0000062587 scopus 로고    scopus 로고
    • Neural network approach to blind separation and enhancement of images
    • G. Ramponi et al., Eds. Trieste, Italy: EURASIP/LINT Publ.
    • A. Cichocki et al., "Neural network approach to blind separation and enhancement of images," in Signal Processing VIII: Theories and Applications, G. Ramponi et al., Eds. Trieste, Italy: EURASIP/LINT Publ., 1996, vol. I, pp. 579-582.
    • (1996) Signal Processing VIII: Theories and Applications , vol.1 , pp. 579-582
    • Cichocki, A.1
  • 31
    • 0033720961 scopus 로고    scopus 로고
    • Multiplicative Newton-like algorithm and independent component analysis
    • S.-I. Amari, C. L. Giles, M. Gori, and V. Piuri, Eds., Como, Italy, July 24-27
    • T. Akuzawa, "Multiplicative Newton-like algorithm and independent component analysis," in Proc. IEEE-INNS-ENNS Int. Joint Conf. Neural Networks, vol. 4, S.-I. Amari, C. L. Giles, M. Gori, and V. Piuri, Eds., Como, Italy, July 24-27, 2000, pp. 79-82.
    • (2000) Proc. IEEE-INNS-ENNS Int. Joint Conf. Neural Networks , vol.4 , pp. 79-82
    • Akuzawa, T.1
  • 32
    • 0038735446 scopus 로고    scopus 로고
    • New fast factorization method for multivariate optimization and its realization as ICA algorithm
    • T.-W. Lee, T.-P. Jung, S. Makeig, and T. J. Sejnowski, Eds., San Diego, CA, Dec. 9-13
    • T. Akuzawa, "New fast factorization method for multivariate optimization and its realization as ICA algorithm," in Proc. Int. Conf. Independent Component Analysis Signal Separation, T.-W. Lee, T.-P. Jung, S. Makeig, and T. J. Sejnowski, Eds., San Diego, CA, Dec. 9-13, 2001, pp. 114-119.
    • (2001) Proc. Int. Conf. Independent Component Analysis Signal Separation , pp. 114-119
    • Akuzawa, T.1
  • 33
    • 0030417779 scopus 로고    scopus 로고
    • Equivariant adaptive source separation
    • Dec.
    • J.-F. Cardoso and B. H. Laheld, "Equivariant adaptive source separation," IEEE Trans. Signal Processing, vol. 44, pp. 3017-3030, Dec. 1996.
    • (1996) IEEE Trans. Signal Processing , vol.44 , pp. 3017-3030
    • Cardoso, J.-F.1    Laheld, B.H.2
  • 34
    • 0000396062 scopus 로고    scopus 로고
    • Natural gradient works efficiently in learning
    • Feb.
    • S. Amari, "Natural gradient works efficiently in learning," Neural Comput., vol. 10, no. 2, pp. 251-276, Feb. 1998.
    • (1998) Neural Comput. , vol.10 , Issue.2 , pp. 251-276
    • Amari, S.1
  • 35
    • 1542603298 scopus 로고    scopus 로고
    • On conjugate gradient-like methods for eigen-like problems
    • A. Edelman and S. T. Smith, "On conjugate gradient-like methods for eigen-like problems," BIT Numer. Math., vol. 36, pp. 494-508, 1996.
    • (1996) BIT Numer. Math. , vol.36 , pp. 494-508
    • Edelman, A.1    Smith, S.T.2
  • 36
    • 0038735445 scopus 로고    scopus 로고
    • Blind signal separation based on the derivatives of the output cumulants and a conjugate gradient algorithm
    • T.-W. Lee, T.-P. Jung, S. Makeig, and T. J. Sejnowski, Eds., San Diego, CA, Dec. 9-13
    • R. Martin-Clemente, C. G. Puntonet, and J. I. Acha, "Blind signal separation based on the derivatives of the output cumulants and a conjugate gradient algorithm," in Proc. Int. Conf. Independent Component Analysis Signal Separation, T.-W. Lee, T.-P. Jung, S. Makeig, and T. J. Sejnowski, Eds., San Diego, CA, Dec. 9-13, 2001, pp. 390-393.
    • (2001) Proc. Int. Conf. Independent Component Analysis Signal Separation , pp. 390-393
    • Martin-Clemente, R.1    Puntonet, C.G.2    Acha, J.I.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.