Moving Average Estimator Least Mean Square Using Echo Cancellation Algorithm
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.
KeywordsEcho cancellation Moving average estimator Least mean square (LMS) filter Adaptive filter Noise cancellation
This work was supported by the Gachon University research fund of 2012. (GCU-2012-R168).
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