Independent component analysis, a new concept?
Signal Processing - Special issue on higher order statistics
Blind source separation for convolutive mixtures
Signal Processing
Entropy Optimization - Application to Blind Source Separation
ICANN '97 Proceedings of the 7th International Conference on Artificial Neural Networks
Signal separation by symmetric adaptive decorrelation: stability,convergence, and uniqueness
IEEE Transactions on Signal Processing
Source separation using a criterion based on second-orderstatistics
IEEE Transactions on Signal Processing
Equivariant adaptive source separation
IEEE Transactions on Signal Processing
An Adaptive Method for Subband Decomposition ICA
Neural Computation
Signal Processing - Special issue: Information theoretic signal processing
Enhancement of source independence for blind source separation
ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation
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Blind Source Separation (BSS) is a basic problem in signal processing. In this paper, we present a new method for separating convolutive mixtures based on the minimization of the output mutual information. We also introduce the concept of joint score function, and derive its relationship with marginal score function and independence. The new approach for minimizing the mutual information is very efficient, although limited by multivariate distribution estimations.