1 |
T. Ristaniemi and, J. Joutsensalo, 'On the performance of blind source separation in COMA downlink,' Proc. Int. Workshop on Independent Analysis and Signal Separation (ICA ' 99), 437-441, Aussois, France, 1999
|
2 |
A. Hyvarinen, J. Karhnen, and E. Oja, Independent Component Analysis, John Wiley & Sons, 2001
|
3 |
A. J. Bell and T. J. Sejnowski, 'An information-maximization approach to blind separation and blind deconvolution,' Neural Computation, 7 (6) 1129-1159, 1995
DOI
ScienceOn
|
4 |
K. Zhang, L. Chan, 'Dimension reduction as a deflation method in ICA,' IEEE Signal proc. Letters, 13 (1) 2006
|
5 |
R. Mukai, S. Araki, and S. Makino, 'Separation and dereverberation performance of frequency domain blind source separation,' Proc. ICA 2001, (Second International Conference on Independent Component Analysis and Blind Signal Separation), 230-235. 2001
|
6 |
S. Araki, S. Makino, H. Sawada and R. Mukai, 'Underdetermined blind separation of convolutive mixtures of speech with directivity pattern based mask and ICA,' Proc. ICA 2004 (Fifth International Conference on Independent Component Analysis and Blind Signal Separation), 898-905, 2004
|
7 |
Q. Lv and X. Zhang, 'A unified method for blind separation of sparse sources with unknown source number,' IEEE Signal proc, Letters, 13 (1) 2006
|
8 |
S.Y. Low, S.Nordholm, and R. Togneri, 'Convolutive blind signal separation with post-processing,' IEEE Trans. On speech and audio processing, 12 (5) 2004
|
9 |
I. Jang, K. Kang, S. Kim and S. Choi, 'F-SEONS: A second-order frequency-domain algorithm for noisy convolutive source separation,' Proc. IEEE Int'I Symposium on Circuit and Systems (ISCAS), 3595-3598, Kobe, Japan, 23-26, 2005
|
10 |
S. Makeig, T. Jung, A.J. Bell, D. Ggahremani and, T. J. Seijnowski, 'Blind separation of auditory event-related brain response into independent components,' Proceedings on National Academic Science. USA, 10979-10984, 1997
|
11 |
S. I. Amari, A. Cichocki and H. H. Yang, 'A new learning algorithm for blind signal separation,' Advances in neural information Processing systems 8. MIT Press, Cambridge, MA
|
12 |
R. Mukai, S. Araki, H. Sawada and S. Makino, 'Removal of residual crosstalk components in blind source separation using time-delayed spectral subtraction,' Proc. ICASSP 2002, 1789-1792, 2002
|
13 |
T.W. Lee, A.J.Bell and, R.Orglmeister, 'Blind source separation of real world signals,' Neural Networks, International Conference on 4, 2129-2134, 1997
|
14 |
C. Fancourt, and L. Parra, 'The generalized sidelobe decorrelator,' IEEE Workshop on the Applications of Signal Processing to Audio and Acoustics, 167-170, 21-24 2001
|
15 |
J. F. Cordoso, 'Blind source separation: statistical principles,' Proc. IEEE, 9 2009-2025, 1998
|
16 |
T. W. Lee, M. Girolami, A. J. Bell, and T. J. Sejonwski, 'A unifying information-theoretic framework for independent component analysis,' Computers and Mathematics with Applications, 31 (11) 1-12, 2000
|
17 |
P. Smaragdis, 'Blind separation of convolved mixtures in the frequency domain,' Nerucomputing, 22 21-34, 1998
DOI
ScienceOn
|
18 |
R. Mukai, S. Araki, H. Sawada and S. Makino, 'Removal of residual crosstalk components in blind source separation using LMS filters,' Proc. NNSP 2002, 435-444, 2002
|
19 |
S. Haykin, Adaptive Filter Theory, Chap. 2, Third Edition, Prentice Hall Inc, NJ 1996
|
20 |
S. Araki, S. Makino, T. Nishikawa and H. and Saruwatari, 'Fundamental limitation of frequency domain blind separation for convolutive of speech,' Proc. ICASSP 2001, 2737-2740, 2001
|