Nonlinearity-robust linear acoustic echo canceller using the maximum Correntropy criterion


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Merabti, H., Massicotte, D. et Zhu, W. P. (2019, December 10-12). Nonlinearity-robust linear acoustic echo canceller using the maximum Correntropy criterion. Dans 2019 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), Ajman, United Arab Emirates DOI 10.1109/ISSPIT47144.2019.9001737.

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For the problem of acoustic echo cancellation (AEC) with nonlinear distortions, we propose to use a linear adaptive filter that maximizes the Correntropy similarity measure instead of the conventional minimization of the mean squared error (MSE) criterion. The maximum Correntropy criterion (MCC) offers robustness to outliers and impulsive noise, which is interesting for the case of speech signal coupled with nonlinearities. To assess the performance of the algorithm, we consider a hard-clipping memoryless saturation nonlinearity. Our simulation results show very interesting performance of the normalized MCC-based linear adaptive filter for the echo return loss enhancement (ERLE) and misalignment measures compared to the MSE-based normalized least mean squares (NLMS) approach. Furthermore, the NMCC adaptive filter has a similar computational complexity as the NLMS algorithm, which makes it very attractive in practical implementations.

Type de document: Document issu d'une conférence ou d'un atelier
Mots-clés libres: Acoustic echo cancellation Nonlinear systems Adaptive filtering Correntropy Mean squared error
Date de dépôt: 09 mai 2022 19:34
Dernière modification: 09 mai 2022 19:34

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