توضیحات
پروژه شبیه سازی الگوریتم تطبیقی اکو پراکنده با متلب:
Abstract
The cancellation of echoes is a vital component of telephony networks. In some cases the echo esponse 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. r 2005 Elsevier B.V. All rights reserved
Keywords: Echo cancellation; Adaptive filters; Sparse system identification
نکات قابل ذکر:
- پروژه شبیه سازی الگوریتم تطبیقی اکو پراکنده با متلب توسط کارشناسان گروه ۱.۲.۳ پروژه پیاده سازی گردیده و به تعداد محدودی قابل فروش می باشد.
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