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Volumn 3, Issue , 2007, Pages 999-1003

A NMF algorithm for blind separation of uncorrelated signals

Author keywords

BSS; NMF; Uncorrelated sources

Indexed keywords

FACTORIZATION; MATRIX ALGEBRA; PATTERN RECOGNITION; WAVELET ANALYSIS;

EID: 45149126075     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICWAPR.2007.4421577     Document Type: Conference Paper
Times cited : (21)

References (12)
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    • A. Hyvärinen, J. Karhunen, and E. Oja, Independent Component Analysis. John Wiley and Sons, 2001 John. B. Author, and A. Friend, Journal paper's name, Journal's name, 39, No. 1, pp. 222-226, Feb. 2001.
    • A. Hyvärinen, J. Karhunen, and E. Oja, Independent Component Analysis. John Wiley and Sons, 2001 John. B. Author, and A. Friend, "Journal paper's name", Journal's name, Vol. 39, No. 1, pp. 222-226, Feb. 2001.
  • 3
    • 3142702668 scopus 로고    scopus 로고
    • Blind Separation of Positive Sources by Globally Convergent Gradient Search
    • E. Oja and M. Plumbley, Blind Separation of Positive Sources by Globally Convergent Gradient Search, Neural Computation, vol. 16, pp. 1811-1825, 2004.
    • (2004) Neural Computation , vol.16 , pp. 1811-1825
    • Oja, E.1    Plumbley, M.2
  • 4
    • 0038460232 scopus 로고    scopus 로고
    • Algorithms for nonnegative independent component analysis
    • M. D. Plumbley, Algorithms for nonnegative independent component analysis, Neural Networks, IEEE Transactions on, vol. 14, pp. 534-543, 2003.
    • (2003) Neural Networks, IEEE Transactions on , vol.14 , pp. 534-543
    • Plumbley, M.D.1
  • 5
    • 33947675352 scopus 로고    scopus 로고
    • New Algorithms for Non-Negative Matrix Factorization in Applications to Blind Source Separation
    • Andrzej Cichocki, R. Z. S.-i. A., New Algorithms for Non-Negative Matrix Factorization in Applications to Blind Source Separation, ICASSP 2006 Proceedings, pp. 621-624, 2006.
    • (2006) ICASSP 2006 Proceedings , pp. 621-624
    • Andrzej Cichocki, R.Z.S.-I.A.1
  • 6
    • 0033592606 scopus 로고    scopus 로고
    • Learning the Parts of Objects by Nonnegative Matrix Factorization
    • D.D. Lee and H.S. Seung, Learning the Parts of Objects by Nonnegative Matrix Factorization, Nature, vol. 401, pp. 788-791,1999.
    • (1999) Nature , vol.401 , pp. 788-791
    • Lee, D.D.1    Seung, H.S.2
  • 7
    • 0028561099 scopus 로고
    • Positive matrix factorization: A non-negative factor model with optimal utilization of error estimates of data values
    • Paatero, P., Tapper, U., Positive matrix factorization: A non-negative 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
  • 9
    • 84900510076 scopus 로고    scopus 로고
    • Nonnegative Matrix Factorization with Sparseness Constraints
    • P.O. Hoyer, Nonnegative Matrix Factorization with Sparseness Constraints, J. Machine Learning Research, vol. 5, pp. 1457-1469, 2004.
    • (2004) J. Machine Learning Research , vol.5 , pp. 1457-1469
    • Hoyer, P.O.1
  • 12
    • 45149087710 scopus 로고    scopus 로고
    • A. Cichocki and R. Zdunek, NMFLAB - MATLAB Toolbox for Non-Negative Matrix Factorization, http://www.bsp.brain.riken.jp/ICALAB/nmfiab.html.
    • A. Cichocki and R. Zdunek, NMFLAB - MATLAB Toolbox for Non-Negative Matrix Factorization, http://www.bsp.brain.riken.jp/ICALAB/nmfiab.html.


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.