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CSDA
2007
169views more  CSDA 2007»
13 years 7 months ago
A null space method for over-complete blind source separation
In blind source separation, there are M sources that produce sounds independently and continuously over time. These sounds are then recorded by m receivers. The sound recorded by ...
Ray-Bing Chen, Ying Nian Wu
ICMCS
2009
IEEE
171views Multimedia» more  ICMCS 2009»
13 years 5 months ago
Optimal joint linear acoustic echo cancelation and blind source separation in the presence of loudspeaker nonlinearity
Acoustic echoes represent a major source of discomfort in hands free, full-duplex, communication systems. The problem becomes particularly difficult when the loudspeakers are nonl...
Mehrez Souden, Zicheng Liu
EAAI
2006
157views more  EAAI 2006»
13 years 7 months ago
Blind source separation based on self-organizing neural network
This contribution describes a neural network that self-organizes to recover the underlying original sources from typical sensor signals. No particular information is required abou...
Anke Meyer-Bäse, Peter Gruber, Fabian J. Thei...
IJON
2002
128views more  IJON 2002»
13 years 7 months ago
Extraction of a source from multichannel data using sparse decomposition
It was discovered recently that sparse decomposition by signal dictionaries results in dramatic improvement of the qualities of blind source separation. We exploit sparse decompos...
Michael Zibulevsky, Yehoshua Y. Zeevi
DSP
2007
13 years 7 months ago
Blind separation of nonlinear mixtures by variational Bayesian learning
Blind separation of sources from nonlinear mixtures is a challenging and often ill-posed problem. We present three methods for solving this problem: an improved nonlinear factor a...
Antti Honkela, Harri Valpola, Alexander Ilin, Juha...