适合定点实现的QRD-LSL自适应算法

C. Paleologu, A. Enescu, S. Ciochină, F. Albu
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引用次数: 2

摘要

在之前的研究中,我们提出了一种适用于定点实现的递归最小二乘(RLS)自适应算法的改进版本。对算法的代价函数使用渐近无偏估计,减小了该参数的动态范围。本文对基于qr分解的最小二乘格(QRD-LSL)自适应算法进行了扩展,该算法是RLS族中“快速”的一员,具有良好的数值性质。减小了算法参数的动态性,便于定点实现。在定点数字信号处理器(DSP)上进行的仿真支持了理论发现的实际方面。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
QRD-LSL Adaptive Alogrithms Suitable for Fixed-Point Implementation
In a previous study we proposed a modified version of the recursive least-square (RLS) adaptive algorithm suitable for fixed-point implementation. Using an asymptotically unbiased estimator for the algorithm's cost function we reduced the dynamic range of this parameter. In this paper, we extend the procedure for the case of QR-decomposition-based least-squares lattice (QRD-LSL) adaptive algorithm, a "fast" member of RLS family, with good numerical properties. The reduced dynamics of the algorithm’s parameters leads to facility for fixed-point implementation. The simulations performed on a fixed-point digital signal processor (DSP) sustain the practical aspects of the theoretical findings.
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