Effect of a Signal Decorrelation on Adaptive Filtering Algorithms for Acoustic Echo Cancellation

被引：0
|
作者：
Hamidia, Mahfoud [1 ]
Amrouche, Abderrahmane [1 ]
机构：
[1] USTHB, Fac Elect & Comp Sci, Speech Commun & Signal Proc Lab, POB 32, Algiers, Algeria
来源：
2017 5TH INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING - BOUMERDES (ICEE-B) | 2017年
关键词：
Acousti echo cancellation (AEC); adaptive filtering; decorrelation; normalized least mean squares (NLMS); convergence speed;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
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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页数：4
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