Moving average estimator least mean square using echo cancellation algorithm
- Authors
- Oh, Sang-Yeob; Ahn, 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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