A modified wavelet-domain adaptive filtering algorithm for stereophonic acoustic echo cancellation in the teleconferencing application

2008 ◽  
Author(s):  
M. Bekrani ◽  
M. Lotfizad
Keyword(s):  
Adaptive Filtering ◽  
Echo Cancellation ◽  
Acoustic Echo Cancellation ◽  
Wavelet Domain ◽  
Filtering Algorithm ◽  
Acoustic Echo

A Variable Mode QR Decomposition Adaptive Filtering Algorithm for Acoustic Echo Cancellation

2014 ◽  
Vol 556-562 ◽  
pp. 3839-3843
Author(s):  
J.B. Li ◽  
C. Lu ◽  
Y. Zhou
Keyword(s):  
Adaptive Filtering ◽  
Input Data ◽  
Qr Decomposition ◽  
Echo Cancellation ◽  
Acoustic Echo Cancellation ◽  
Activity Detection ◽  
Filtering Algorithm ◽  
Acoustic Echo ◽  
Variable Mode ◽  
Voice Activity

This paper studies a new QR decomposition adaptive filtering algorithm for acoustic echo cancellation (AEC). Based on the p-TA-QR-LS algorithm [1] and an efficient voice activity detection technique, the proposed algorithm can distinguish the significant and insignificant input data periods. The resultant variable mode p-TA-QR-LS algorithm can work between two modes (p=1and N) and is thus suitable for AEC application where reusing significant input data can enhance convergence and the computation cost can be saved when the input is relatively weak.

A New Switching QR Decomposition Adaptive Filtering Algorithm for Acoustic Echo Cancellation

2013 ◽  
Vol 303-306 ◽  
pp. 1077-1080
Author(s):  
Yi Zhou ◽  
Q. Li ◽  
T. Q. Zhang
Keyword(s):  
Adaptive Filtering ◽  
Echo Cancellation ◽  
Acoustic Echo Cancellation ◽  
Switching Scheme ◽  
State Estimate ◽  
Filtering Algorithm ◽  
Estimate Error ◽  
Fast Convergence Rate ◽  
Acoustic Echo ◽  
Convergence Performance

This paper proposes a new adaptive filtering algorithm based on the p-TA-QR-LS algorithm [1]. With a coefficient-derivative-based switching scheme, the new algorithm can work between two modes (p=1 and N) and achieve overall optimum convergence performance. The resultant switching p-TA-QR-LS algorithm is thus particularly suitable for acoustic echo cancellation (AEC) where both fast convergence rate and low steady-state estimate error are desired. Experiments are conducted to verify its improved overall convergence performance.

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