Blind separation of instantaneous mixtures of nonstationary sources
IEEE Transactions on Signal Processing
Controlled complete ARMA independent process analysis
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Multichannel nonnegative matrix factorization in convolutive mixtures for audio source separation
IEEE Transactions on Audio, Speech, and Language Processing
A general modular framework for audio source separation
LVA/ICA'10 Proceedings of the 9th international conference on Latent variable analysis and signal separation
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We describe an ICA method based on second order statistics which was originally developed for the separation of components in astrophysical images but is appropriate in contexts where accuracy and versatility are of primary importance. It combines several basic ideas of ICA in a new flexible framework designed to deal with complex data scenarios. This paper describes our approach and discusses its implementation in terms of a library of components.