Title :
A NMF algorithm for blind separation of uncorrelated signals
Author :
Zhang, Ye ; Fang, Yong
Author_Institution :
Shanghai Univ., Shanghai
Abstract :
Most of the proposed algorithms for blind sources separation are not able to extract the source signals when the unknown sources are not mutually statistically independent. In this paper, the blind separation problem for uncorrelated signals is explored. A novel algorithm is proposed based on the nonnegative matrix factorization methods with the least correlated component constraints. The algorithm relaxes the source independence assumption and has low-complexity algebraic computations, and thus is computationally efficient. Simulation results show that the proposed algorithm can provide an efficient separation performance for the uncorrelated source signals.
Keywords :
blind source separation; computational complexity; matrix decomposition; blind sources separation; low-complexity algebraic computations; matrix factorization methods; source independence assumption; uncorrelated signal blind separation; Algorithm design and analysis; Blind source separation; Image processing; Independent component analysis; Information analysis; Pattern analysis; Signal analysis; Signal processing; Source separation; Wavelet analysis; BSS; NMF;
Conference_Titel :
Wavelet Analysis and Pattern Recognition, 2007. ICWAPR '07. International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-1065-1
Electronic_ISBN :
978-1-4244-1066-8
DOI :
10.1109/ICWAPR.2007.4421577