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Blind Separation of rotating machine signals using Penalized Mutual Information criterion and Minimal Distortion Principle
Abstract : The Blind Separation problem of convolutive mixtures is addressed in this paper. We have developed a new algorithm based on a penalized mutual information criterion recently introduced in [El Rhabi et al., A penalized mutual information criterion for blind separation of convolutive mixtures, Signal Processing 84 (2004) 1979–1984] and which also allows to choose an optimal separator among an infinite number of valid separators that can extract the source signals in a certain sense according to the Minimal Distortion Principle. So, the minimisation of this criterion is easily done using a direct gradient approach without constraint on the displacements. Thus, our approach allows to restore directly the contribution of the sources to the sensor signals without post-processing as it is usually done. Finally, we illustrate the performances of our algorithm through simulations and on real rotating machine vibration signals.
Littérature citée [16 références]
https://hal-enpc.archives-ouvertes.fr/hal-01812922
Contributeur : Mohammed El Rhabi <>
Soumis le : mardi 12 juin 2018 - 00:03:43
Dernière modification le : mercredi 21 octobre 2020 - 12:02:02
Archivage à long terme le : : jeudi 13 septembre 2018 - 12:50:52
Contributeur : Mohammed El Rhabi <>
Soumis le : mardi 12 juin 2018 - 00:03:43
Dernière modification le : mercredi 21 octobre 2020 - 12:02:02
Archivage à long terme le : : jeudi 13 septembre 2018 - 12:50:52
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