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BMCBI
2006
129views more  BMCBI 2006»
13 years 7 months ago
Independent Component Analysis-motivated Approach to Classificatory Decomposition of Cortical Evoked Potentials
Background: Independent Component Analysis (ICA) proves to be useful in the analysis of neural activity, as it allows for identification of distinct sources of activity. Applied t...
Tomasz G. Smolinski, Roger Buchanan, Grzegorz M. B...
IJON
2006
131views more  IJON 2006»
13 years 7 months ago
Optimizing blind source separation with guided genetic algorithms
This paper proposes a novel method for blindly separating unobservable independent component (IC) signals based on the use of a genetic algorithm. It is intended for its applicati...
J. M. Górriz, Carlos García Puntonet...
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
2009
IEEE
14 years 2 months ago
A multistage approach for blind separation of convolutive speech mixtures
In this paper, we propose a novel algorithm for the separation of convolutive speech mixtures using two-microphone recordings, based on the combination of independent component an...
Tariqullah Jan, Wenwu Wang, DeLiang Wang
ICA
2012
Springer
12 years 3 months ago
Distributional Convergence of Subspace Estimates in FastICA: A Bootstrap Study
Independent component analysis (ICA) is possibly the most widespread approach to solve the blind source separation (BSS) problem. Many different algorithms have been proposed, tog...
Jarkko Ylipaavalniemi, Nima Reyhani, Ricardo Vig&a...