块LMS算法跟踪性能的舍入误差分析

Proceedings of the Sixteenth National Radio Science Conference. NRSC'99 (IEEE Cat. No.99EX249) Pub Date : 1999-02-23 DOI:10.1109/NRSC.1999.760914

E. Eweda, W. Younis, S. El-Ramly

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引用次数: 2

摘要

分析了块最小均方算法在对时变目标进行自适应辨识时，舍入误差对算法跟踪性能的影响。假设四舍五入量化。导出了稳态均方误差、稳态均方权值偏差及相应的最佳步长表达式。结果表明，均方误差和均方权值偏差是滤波系数字长和算法块大小的递减函数。导出了最小和最大块长度的表达式。并与传统LMS算法的性能进行了比较。结果表明，BLMS算法比LMS算法具有更高的抗舍入误差能力。通过计算机仿真验证了本文的理论结果。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Roundoff error analysis of the tracking performance of the block LMS algorithm

The paper is concerned with analyzing the roundoff error effect on the tracking performance of the block least mean square (BLMS) algorithm when used in the adaptive identification of a time-varying plant. Rounding quantization is assumed. Expressions are derived for the steady state mean square error, steady state mean square weight deviation, and the corresponding optimum step sizes. It is found that the mean square error and the mean square weight deviation are decreasing functions of both the filter coefficients wordlength and the algorithm block size. Expressions for minimum and maximum block lengths are derived. The performance of the BLMS is compared to that of the conventional LMS algorithm. It is found that the BLMS possesses a higher resistance to roundoff errors than the LMS algorithm. The theoretical results of the paper are validated by computer simulations.

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Proceedings of the Sixteenth National Radio Science Conference. NRSC'99 (IEEE Cat. No.99EX249)

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