An Efficient, Fast Converging Adaptive Filter for Network Echo Cancellation

Steven L. Grant, Missouri University of Science and Technology

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This paper discusses a fast efficient adaptive filtering algorithm for network echo cancellers PNLMS++ (proportionate normalized least mean squares ++). Compared to the conventional normalized least mean squares (NLMS) algorithm, PNLMSI++ converges much more quickly when the echo path is sparse. When the echo path is dispersive, the convergence rate is the same as NLMS. In addition, the new algorithm diverges at the same rate and to the same misalignment level as NLMS during periods of undetected double-talk. PNLMS++ is only 50% more computationally complex than NLMS and requires no additional memory