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dc.contributor.authorLiu, Xianhua
dc.contributor.authorCardoso, J.
dc.contributor.authorRandall, R.
dc.identifier.citationLiu, Xianhua and Cardoso, Jean-Francois and Randall, Robert B. 2010. Very fast blind source separation by signal to noise ratio based stopping threshold for the SHIBBS/SJAD algorithm. Mechanical Systems and Signal Processing. 24 (7): pp. 2096-2103.

This paper works on joint approximate diagonalization of simplified fourth order cumulant matrices for very fast and large scale blind separation of instantaneous mixing model sources. The JADE algorithm is widely accepted but only limited to small scale separation tasks. The SHIBBS algorithm calculates a fraction of the fourth order cumulant set and avoids eigenmatrix decomposition to reduce calculation cost. However, it was seen to be slower than JADE at the time of its first publication and is hence less known. On the other hand, the SJAD algorithm using the same approach is shown to be very fast. This paper studies the iteration convergence criterion and proposes to use a signal to noise ratio based iteration stopping threshold approach. The improved SHIBBS/SJAD algorithm is very fast, and capable of large scale separation. Experimental separation comparisons between the SHIBBS/SJAD and FastICA are presented.

dc.subjectIndependent component analysis
dc.subjectBlind source separation
dc.subjectSignal to noise ratio
dc.subjectJoint approximate diagonalization
dc.subjectFourth order cumulant matrices
dc.titleVery fast blind source separation by signal to noise ratio based stopping threshold for the SHIBBS/SJAD algorithm
dc.typeJournal Article
dcterms.source.titleMechanical Systems and Signal Processing
curtin.accessStatusFulltext not available

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