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71
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ISCAS
2005
IEEE
131views Hardware» more  ISCAS 2005»
15 years 3 months ago
Blind signal separation into groups of dependent signals using joint block diagonalization
— Multidimensional or group independent component analysis describes the task of transforming a multivariate observed sensor signal such that groups of the transformed signal com...
Fabian J. Theis
IJON
2006
180views more  IJON 2006»
14 years 9 months ago
Nonnegative independent component analysis based on minimizing mutual information technique
A novel neural network technique for nonnegative independent component analysis is proposed in this letter. Compared with other algorithms, this method can work efficiently even w...
Chun-Hou Zheng, De-Shuang Huang, Zhan-Li Sun, Mich...
ISCAS
2005
IEEE
214views Hardware» more  ISCAS 2005»
15 years 3 months ago
Blind separation of statistically independent signals with mixed sub-Gaussian and super-Gaussian probability distributions
— In the context of Independent Component Analysis (ICA), we propose a simple method for online estimation of activation functions in order to blindly separate instantaneous mixt...
Muhammad Tufail, Masahide Abe, Masayuki Kawamata
85
Voted
ICML
2007
IEEE
15 years 10 months ago
Nonlinear independent component analysis with minimal nonlinear distortion
Nonlinear ICA may not result in nonlinear blind source separation, since solutions to nonlinear ICA are highly non-unique. In practice, the nonlinearity in the data generation pro...
Kun Zhang, Laiwan Chan
ISMIR
2005
Springer
215views Music» more  ISMIR 2005»
15 years 3 months ago
Separation of Vocals from Polyphonic Audio Recordings
Source separation techniques like independent component analysis and the more recent non-negative matrix factorization are gaining widespread use for the monaural separation of in...
Shankar Vembu, Stephan Baumann