A fast fixed-point algorithm for independent component analysis
Neural Computation
A Method for Filter Shaping in Convolutive Blind Source Separation
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
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This paper presents a new algorithm for solving the permutation ambiguity in convolutive blind source separation. When transformed to the frequency domain, the source separation problem reduces to independent instantaneous separation in each frequency bin, which can be efficiently solved by existing algorithms. But this independency leads to the problem of correct alignment of these single bins which is still not entirely solved. The algorithm proposed in this paper models the frequency-domain separated signals using the generalized Gaussian distribution and utilizes the small deviation of the exponent between neighboring bins for the detection of correct permutations.