多核单元处理器中最小二乘多谐拟合算法的实现

José Maria Santos, P. Ramos
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引用次数: 1

摘要

最小二乘(LS)方法将特定数据模型与获取的数据集之间的最小二乘误差最小化。这是正弦拟合算法的情况,用于确定最适合采集信号的正弦波参数。在具有多个谐波的信号的情况下,可以使用类似正弦拟合算法的多谐波拟合算法来估计谐波的幅度和相位。本文介绍了利用多核Cell处理器实现LS多谐波拟合算法,确定多谐波信号的基频,然后确定谐波幅值和相位。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Implementation of a least-squares multi-harmonic fitting algorithm in the multicore cell processor
Least squares (LS) methods minimize the LS error between a specific data model and an acquired data set. This is the case of sine-fitting algorithms, which are used to determine the sine wave parameters that best fit an acquired signal. In the case of signals with multiple harmonics, one can use a multi-harmonic fitting algorithm resembling the sine-fitting algorithm to estimate the amplitudes and phases of the harmonics. This paper describes the implementation of a LS multi-harmonic fitting algorithm using the multicore Cell processor to determine the fundamental frequency of a multi-harmonic signal and then the harmonic amplitudes and phases.
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