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Fetal electrocardiogram extraction by sequential source separation in the wavelet domain

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journal contribution
posted on 2010-01-11, 12:51 authored by Maria G. Jafari, Jonathon Chambers
This work addresses the problem of fetal electrocardiogram extraction using blind source separation (BSS) in the wavelet domain. A new approach is proposed, which is particularly advantageous when the mixing environment is noisy and time-varying, and that is shown, analytically and in simulation, to improve the convergence rate of the natural gradient algorithm. The distribution of the wavelet coefficients of the source signals is then modeled by a generalized Gaussian probability density, whereby in the time-scale domain the problem of selecting appropriate nonlinearities when separating mixtures of both sub- and super-Gaussian signals is mitigated, as shown by experimental results.



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JAFARI, M.G. and CHAMBERS, J., 2005. Fetal electrocardiogram extraction by sequential source separation in the wavelet domain. IEEE Transactions on Biomedical Engineering, 52 (3), pp. 390-400




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This is an article from the journal, IEEE Transactions on Biomedical Engineering [© IEEE]. It 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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