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Overcomplete source separation using Laplacian mixture models

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2 Author(s)
N. Mitianoudis ; Electr. & Electron. Eng. Dept., Imperial Coll. London, UK ; T. Stathaki

The authors explore the use of Laplacian mixture models (LMMs) to address the overcomplete blind source separation problem in the case that the source signals are very sparse. A two-sensor setup was used to separate an instantaneous mixture of sources. A hard and a soft decision scheme were introduced to perform separation. The algorithm exhibits good performance as far as separation quality and convergence speed are concerned.

Published in:

IEEE Signal Processing Letters  (Volume:12 ,  Issue: 4 )