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Adaptive algorithms for sparse echo cancellation

机译：稀疏回声消除的自适应算法

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The cancellation of echoes is a vital component of telephony networks. In some cases the echo response that must be identified by the echo canceller is sparse, as for example when telephony traffic is routed over networks with unknown delay such as packet-switched networks. The sparse nature of such a response causes standard adaptive algorithms including normalized LMS to perform poorly. This paper begins by providing a review of techniques that aim to give improved echo cancellation performance when the echo response is sparse. In. addition, adaptive filters can also be designed to exploit sparseness in the input signal by using partial update procedures. This concept is discussed and the MMax procedure is reviewed. We proceed to present a new high performance sparse adaptive algorithm and provide comparative echo cancellation results to show the relative performance of the existing and new algorithms. Finally, an efficient low cost implementation of our new algorithm using partial update adaptation is presented and evaluated. This algorithm exploits both sparseness of the echo response and also sparseness of the input signal in order to achieve high performance without high computational cost. (c) 2005 Elsevier B.V. All rights reserved.
机译：回声的消除是电话网络的重要组成部分。在某些情况下，必须由回声消除器识别的回声响应是稀疏的，例如，当电话业务通过未知延迟的网络（例如，分组交换网络）路由时。这种响应的稀疏性质导致标准的自适应算法（包括归一化的LMS）表现不佳。本文首先提供了一些技术综述，旨在在回声响应稀疏时提高回声消除性能。在。此外，还可以将自适应滤波器设计为通过使用部分更新程序来利用输入信号中的稀疏性。讨论了此概念，并审查了MMax程序。我们继续提出一种新的高性能稀疏自适应算法，并提供比较的回声消除结果，以显示现有算法和新算法的相对性能。最后，提出并评估了使用部分更新自适应的新算法的高效低成本实现。该算法既利用了回声响应的稀疏性，又利用了输入信号的稀疏性，以实现高性能而又不增加计算成本。 （c）2005 Elsevier B.V.保留所有权利。

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