Abstract
We present a two-stage algorithm to perform blind source separation of sources organized in subspaces, where sources in different subspaces have zero phase synchrony and sources in the same subspace have full phase synchrony. Typical separation techniques such as ICA are not adequate for such signals, because phase-locked signals are not independent. We demonstrate the usefulness of this algorithm on a simulated dataset. The results show that the algorithm works very well in low-noise situations. We also discuss the necessary improvements to be made before the algorithm is able to deal with real-world signals.
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Almeida, M., Bioucas-Dias, J., Vigário, R. (2010). Independent Phase Analysis: Separating Phase-Locked Subspaces. 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_24
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DOI: https://doi.org/10.1007/978-3-642-15995-4_24
Publisher Name: Springer, Berlin, Heidelberg
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