改进的FxLMS算法,提高了收敛性能

M. Rupp, A. H. Sayed
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引用次数: 33

摘要

本文提出了FxLMS算法的两种改进,改进了收敛性,尽管与原始FxLMS更新相同的计算成本是每时间步2M次操作。本文进一步介绍了一种广义的FxLMS递归,并证明了各种递归实际上都是滤波误差形式。给出了保证快速收敛的步长参数的最优选择和鲁棒性的条件。文中给出了几个仿真结果来说明本文的讨论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modified FxLMS algorithms with improved convergence performance
This paper proposes two modifications of the FxLMS algorithm with improved convergence behaviour albeit at the same computational cost of 2M operations per time step as the original FxLMS update. The paper further introduces a generalized FxLMS recursion and establishes that the various recursions are in fact of filtered-error form. An optimal choice of the step-size parameter in order to guarantee faster convergence, and conditions for robustness, are also derived. Several simulation results are included to illustrate the discussions.
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