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» Source Separation with Gaussian Process Models
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ICASSP
2010
IEEE
13 years 7 months ago
HMM-based separation of acoustic transfer function for single-channel sound source localization
This paper presents a sound source (talker) localization method using only a single microphone, where a HMM (Hidden Markov Model) of clean speech is introduced to estimate the aco...
Ryoichi Takashima, Tetsuya Takiguchi, Yasuo Ariki
ISCAS
2005
IEEE
214views Hardware» more  ISCAS 2005»
14 years 1 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
WAA
2001
Springer
13 years 12 months ago
Skewness of Gabor Wavelets and Source Signal Separation
Responses of Gabor wavelets in the mid-frequency space build a local spectral representation scheme with optimal properties regarding the time-frequency uncertainty principle. How...
Weichuan Yu, Gerald Sommer, Konstantinos Daniilidi...
ICASSP
2011
IEEE
12 years 11 months ago
On the relation between ICA and MMSE based source separation
This paper aims at deriving a relationship between minimum mean square error (MMSE) based source separation and independent component analysis (ICA) based on the Kullback-Leibler ...
Benedikt Loesch, Bin Yang
ICASSP
2008
IEEE
14 years 1 months ago
Extension of EFICA algorithm for blind separation of piecewise stationary non Gaussian sources
We propose an extension of EFICA algorithm for piecewise stationary and non Gaussian signals. The proposed method is able to profit from varying distribution of the original sign...
Zbynek Koldovský, Jirí Málek,...