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Sequential blind source extraction for quasi-periodic signals with time-varying period

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journal contribution
posted on 2009-11-24, 14:29 authored by Thato K. Tsalaile, Reza Sameni, Saeid Sanei, Christian Jutten, Jonathon Chambers
A novel second-order-statistics-based sequential blind extraction algorithm for blind extraction of quasi-periodic signals, with time-varying period, is introduced in this paper. Source extraction is performed by sequentially converging to a solution that effectively diagonalizes autocorrelation matrices at lags corresponding to the time-varying period, which thereby explicitly exploits a key statistical nonstationary characteristic of the desired source. The algorithm is shown to have fast convergence and yields significant improvement in signal-to-interference ratio as compared to when the algorithm assumes a fixed period. The algorithm is further evaluated on the problem of separation of a heart sound signal from real-world lung sound recordings. Separation results confirm the utility of the introduced approach, and listening tests are employed to further corroborate the results.



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TSALAILE, T. ... et al, 2009. Sequential blind source extraction for quasi-periodic signals with time-varying period. IEEE Transactions on Biomedical Engineering, 56 (3), pp. 646-655.




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This article was published in the journal IEEE Transactions on Biomedical Engineering [© IEEE] and is also available at: http://ieeexplore.ieee.org/ Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.




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