Abstract
We recently proposed a new method based on spectral decorrelation for blindly separating linear instantaneous mixtures of non-stationary sources. In this paper, we propose a generalization of this method to FIR convolutive mixtures using a second-order approach based on block-diagonalization of covariance matrices in the frequency domain. Contrary to similar time or time-frequency domain methods, our approach requires neither the piecewise stationarity of the sources nor their sparseness. The simulation results show the better performance of our approach compared to these methods.
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References
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Saylani, H., Hosseini, S., Deville, Y. (2010). Blind Separation of Convolutive Mixtures of Non-stationary Sources Using Joint Block Diagonalization in the Frequency Domain. In: Vigneron, V., Zarzoso, V., Moreau, E., Gribonval, R., Vincent, E. (eds) Latent Variable Analysis and Signal Separation. LVA/ICA 2010. Lecture Notes in Computer Science, vol 6365. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15995-4_13
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DOI: https://doi.org/10.1007/978-3-642-15995-4_13
Publisher Name: Springer, Berlin, Heidelberg
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