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Acoustic Echo Cancellation Using Variable Step Size Based Adaptive Filtering with Performance Measure

机译:基于可变步长的自适应回声消除与性能测度

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Acoustic echo is a most frequent occurrence in modern telecommunication systems. This paper describes the different adaptive filtering algorithms to minimize an unwanted echo and improves quality of speech signals. Adaptive filtering has been an active area of research. Here we are using NLMS, MMAX-NLMS and MMAX-NLMSvss algorithms to analyze speech signal. In both NLMS and MMAX-NLMS algorithms the step size parameter is fixed. That forces a performance compromise between fast convergence and small steady state misadjustment. So, Partial update adaptive algorithms have been proposed by deriving a variable step-size for the MMAX-NLMS algorithm using its mean square deviation. The proposed MMAX-NLMSvss algorithm is tested with speech input signal and the result shows that it has fast convergence time, lower intricacy compared to the NLMS, MMAX-NLMS algorithm.
机译:回声是现代电信系统中最常见的情况。本文介绍了不同的自适应滤波算法,以最大程度地减少不必要的回声并提高语音信号的质量。自适应滤波一直是研究的活跃领域。在这里,我们使用NLMS,MMAX-NLMS和MMAX-NLMSvss算法来分析语音信号。在NLMS和MMAX-NLMS算法中,步长参数都是固定的。这迫使性能在快速收敛和较小的稳态失调之间进行折衷。因此,通过使用均方偏差为MMAX-NLMS算法推导可变步长,已提出了部分更新自适应算法。用语音输入信号对提出的MMAX-NLMSvss算法进行了测试,结果表明,与NLMS,MMAX-NLMS算法相比,该算法收敛速度快,复杂度较低。

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