Effect of a signal decorrelation on adaptive filtering algorithms for acoustic echo cancellation

Mahfoud Hamidia,Abderrahmane Amrouche

doi:10.1109/icee-b.2017.8192114

Effect of a signal decorrelation on adaptive filtering algorithms for acoustic echo cancellation

Mahfoud Hamidia, Abderrahmane Amrouche

https://doi.org/10.1109/icee-b.2017.8192114

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Publication Date: Oct 1, 2017

Citations: 9

Affiliation: University of Algiers Benyoucef Benkhedda, University of Sciences and Technology Houari Boumediene

#Normalized Least Mean Squares #Algorithms For Acoustic Echo Cancellation + Show 8 more

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Abstract

Acoustic echo cancellation (AEC) is a well-known issue in voice communication systems; it is used to reduce undesired echoes. Adaptive filtering is generally employed for AEC. However, the performances of adaptive filtering algorithms are limited for a correlated input signal. This paper presents the effect of an input signal decorrelation on the performances of adaptive filtering algorithms for AEC application. Therefore, normalized least mean squares (NLMS) algorithm is used, performed by: USASI noise and speech signals. Simulation results show an improvement in term of convergence speed of NLMS algorithm for the decorrelated signal compared to the original signal.

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