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Moving average estimator least mean square using echo cancellation algorithm

Authors
Oh, Sang-YeobAhn, Chan-Shik
Issue Date
Jan-2013
Publisher
Springer, Dordrecht
Keywords
Adaptive filter; Echo cancellation; Least mean square (LMS) filter; Moving average estimator; Noise cancellation
Citation
Lecture Notes in Electrical Engineering, v.215 LNEE, pp.319 - 324
Journal Title
Lecture Notes in Electrical Engineering
Volume
215 LNEE
Start Page
319
End Page
324
URI
https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/14893
DOI
10.1007/978-94-007-5860-5_38
ISSN
1876-1100
Abstract
Eco cancellation algorithm should not only promptly adapt itself to changing environment but also minimize effects of a speech signal. However, since the color noise does not feature a consistent signal, it certainly has a significant influence on the speech signal. In this paper, the echo cancellation algorithm with a moving average LMS filter applied has been proposed. For the color noise cancellation method, an average estimator was measured by LMS adaptation filter techniques while a LMS filter step size was controlled. In addition, as it was designed to converge on a non-noise signal, the echo signal was cancelled which would, in return, lead it to the improvement of a performance. For the color noise environment, the echo cancellation Algorithm with the Average Estimator LMS filter used was applied and, a result to prove a convergence performance and stability to be improved by 10 dB comparing to the current method was gained. © 2013 Springer Science+Business Media.
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Oh, Sang Yeob
College of IT Convergence (컴퓨터공학부(컴퓨터공학전공))
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