When is non-negative matrix decomposition unique?

CISS 2008, The 42nd Annual Conference on Information Sciences and Systems

Volumn , Issue , 2008, Pages 1091-1092

  Rickard, Scott ^a   Cichocki, Andrzej ^b  

^a UNIVERSITY COLLEGE DUBLIN   (Ireland)

^b RIKEN BRAIN SCIENCE INSTITUTE   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

BLIND SOURCE SEPARATION; COMMUNICATION; CYBERNETICS; FACTORIZATION; INFORMATION MANAGEMENT; INFORMATION SCIENCE;

ACTIVE COMPONENTS; ANNUAL CONFERENCE; DEMIXING PROCESS; LINEAR COMBINATIONS; NEGATIVE COMPONENTS; NON-NEGATIVE MATRICES; NON-NEGATIVE MATRIX FACTORIZATION; SOLUTION SPACES; UNIQUE DECOMPOSITION; UNIQUE SOLUTION;

MATRIX ALGEBRA;

EID: 51849087384     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CISS.2008.4558681     Document Type: Conference Paper

References (4)

1. O. Yilmaz and S. Rickard, "Blind separation of speech mixtures via time-frequency masking," IEEE Transactions on Signal Processing, vol. 52, no. 7, pp. 1830-1847, July 2004.
2. M. D. Plumbley, "Conditions for nonnegative independent component analysis," IEEE Signal Processing Letter, vol. 9, no. 6, pp. 177-180, June 2002.
3. C.-H. Zheng, D.-S. Huang, Z.-L. Sun, M. Lyu, and T.-M, Lok, "Non-negative independent component analysis based on minimizing mutual information technique," Neurocomputing, vol. 69, no. 7-9, pp. 878-883, March 2006.
4. D. Donoho and V. Stodden, "When does non-negative matrix factorization give a correct decomposition into parts?" in Advances in Neural Information Processing Systems 16, S. Thrun, L. Saul, and B. Schölkopf, Eds. Cambridge, MA: MIT Press, 2004.