Abstract
Existing methods for frequency-domain estimation of mixing filters in convolutive blind source separation (BSS) suffer from permutation and scaling indeterminacies in sub-bands. However, if the filters are assumed to be sparse in the time domain, it is shown in this paper that the ℓ1-norm of the filter matrix increases as the sub-band coefficients are permuted. With this motivation, an algorithm is then presented which solves the source permutation indeterminacy, provided there is no scaling indeterminacy in sub-bands. The robustness of the algorithm to noise is also presented.
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References
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Sudhakar, P., Gribonval, R. (2009). A Sparsity-Based Method to Solve Permutation Indeterminacy in Frequency-Domain Convolutive Blind Source Separation. In: Adali, T., Jutten, C., Romano, J.M.T., Barros, A.K. (eds) Independent Component Analysis and Signal Separation. ICA 2009. Lecture Notes in Computer Science, vol 5441. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00599-2_43
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DOI: https://doi.org/10.1007/978-3-642-00599-2_43
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-00598-5
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