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Practical variable step-size adaptive algorithms for echo cancellation

机译:用于回声消除的实用可变步长自适应算法

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The most common algorithms used for echo cancellation are the normalized least-mean-square (NLMS) and the affine projection (AP). The classical versions of these algorithms use a constant step-size parameter and need to establish a tradeoff between several performance criteria e.g., high convergence rate versus low misadjustment. In this paper, we present a class of variable step-size NLMS and AP algorithms, which are designed to recover the near-end signal from the error of the adaptive filter. The simulation results indicate a robust behavior of these algorithms against the presence of the near-end signal.
机译:用于回声消除的最常见算法是归一化最小均线(NLMS)和仿射投影(AP)。这些算法的经典版本使用恒定的步骤大小参数,并且需要在几个性能标准之间建立权衡,例如,高收敛速率与低误诊。在本文中,我们展示了一类变量步长NLM和AP算法,其被设计为从自适应滤波器的误差恢复近端信号。仿真结果表明这些算法对近端信号的存在的鲁棒行为。

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