Common components analysis via linked blind source separation

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Volumn 2015-August, Issue , 2015, Pages 2150-2154

  Zhou, Guoxu ^a   Cichocki, Andrzej ^a   Mandic, Danilo P ^b  

^a RIKEN BRAIN SCIENCE INSTITUTE   (Japan)

^b IMPERIAL COLLEGE LONDON   (United Kingdom)

Author keywords

group independent component analysis; Linked blind source separation; nonnegative matrix factorization

Indexed keywords

AUDIO SIGNAL PROCESSING; FACTORIZATION; INDEPENDENT COMPONENT ANALYSIS; MATRIX ALGEBRA; SPEECH COMMUNICATION;

COMMON FEATURES; INDIVIDUAL COMPONENTS; MULTI BLOCKS; NONNEGATIVE MATRIX FACTORIZATION;

BLIND SOURCE SEPARATION;

EID: 84946043924     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICASSP.2015.7178351     Document Type: Conference Paper

References (15)

1. Y. Li, T. Adali, W. Wang, and V. D. Calhoun, "Joint blind source separation by multiset canonical correlation analysis," IEEE Transactions on Signal Processing, vol. 57, no. 10, pp. 3918-3929, oct. 2009.
2. E. F. Lock, K. A. Hoadley, J. S. Marron, and A. B. No-bel, "Joint and individual variation explained (JIVE) for integrated analysis of multiple data types," The Annals of Applied Statistics, vol. 7, no. 1, pp. 523-542, 2013.
3. C. M. Crainiceanu, B. S. Caffo, S. Luo, V. M. Zipun-nikov, and N. M. Punjabi, "Population value decom-position, a framework for the analysis of image popula-tions," Journal of the American Statistical Association, vol. 106, no. 495, pp. 775-790, 2011.
4. M. Kim, J. Yoo, K. Kang, and S. Choi, "Nonnegative matrix partial co-factorization for spectral and temporal drum source separation," Selected Topics in Signal Pro-cessing, IEEE Journal of, vol. 5, no. 6, pp. 1192-1204, oct. 2011.
5. V. D. Calhoun, J Liu, and T. Adali, "A review of group ICA for fMRI data and ICA for joint inference of imag-ing, genetic, and ERP data," NeuroImage, vol. 45, no. 1, pp. 163-172, 2009.
6. S. Ma, R. Phlypo, V. D. Calhoun, and T. Adali, "Captur-ing group variability using IVA: A simulation study and graph-theoretical analysis," in Proc. IEEE International Conference on Acoustics, Speech, and Signal Process-ing (ICASSP), Vancouver, BC, May 2013.
7. M. Anderson, G. Fu, R. Phlypo, and T. Adali, "Indepen-dent vector analysis: Identification conditions and per-formance bounds," IEEE Transactions on Signal Pro-cessing, vol. 62, no. 17, pp. 4399-4410, Sept 2014.
8. G. H. Golub and C. F. Van Loan, Matrix Computations, Johns Hopkins University Press, 2715 North Charles Street, Baltimore, Maryland, 3 edition, 1996.
9. A. Cichocki and S. Amari, Adaptive Blind Signal and Image Processing: Learning Algorithms and Applica-tions, John Wiley & Sons, Ltd, 2002.
10. F. R. Bach and M. I. Jordan, "Kernel independent com-ponent analysis," Journal of Machine Learning Re-search, vol. 3, pp. 1-48, Mar. 2003.
11. G. Zhou, A. Cichocki, and S. Xie, "Fast nonnegative matrix/tensor factorization based on low-rank approxi-mation," IEEE Transactions on Signal Processing, vol. 60, no. 6, pp. 2928-2940, june 2012.
12. Guoxu Zhou, Andrzej Cichocki, Qibin Zhao, and Shengli Xie, "Nonnegative matrix and tensor factoriza-tions: An algorithmic perspective," IEEE Signal Pro-cessing Magazine, vol. 31, no. 3, pp. 54-65, May 2014.
13. A. Cichocki, S. Amari, K. Siwek, and T. Tanaka, "ICALAB toolbox," 2007.
14. A. Belouchrani, K. AbedMeraim, J. F. Cardoso, and E. Moulines, "A blind source separation technique using second-order statistics," IEEE Transactions on Signal Processing, vol. 45, no. 2, pp. 434-444, Feb 1997.
15. F. Y. Wang, C. Y. Chi, T. H. Chan, and Y. Wang, "Non-negative least-correlated component analysis for sepa-ration of dependent sources by volume maximization," IEEE Transactions on Pattern Analysis and Machine In-telligence, vol. 32, no. 5, pp. 875-888, May 2010.