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Weighted LS estimation of spectral contents and periodicity of signals comprising multi-frequency components

机译:频谱内容的加权LS估计和包含多频分量的信号的周期性

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The goal of this paper is to apply the Weighted Least Squares method to accurately estimate the period and spectral contents of a noisy periodic signal that has many frequency components. The signal data record has a total number of periods that is not necessarily an integer, but is greater than two. There is no need for synchronization between the generator and the data acquisition, where the sampling rates may be different and the number of samples per period may not necessarily be an integer number. The estimation method is invoked by computing the noise variance first from an initial least squares estimate, which is then used for weighting the cost function of the Weighted Least Squares Estimator. It is shown that the accuracy of the estimated results is superior to estimates that are devoid of variance weighting, such as those engendered by the Least Squares Estimator.
机译:本文的目的是应用加权最小二乘法来准确估计具有许多频率成分的嘈杂周期信号的周期和频谱内容。信号数据记录的周期总数不一定是整数,而是大于两个。发生器和数据采集之间无需同步,因为采样率可能不同,每个周期的采样数不一定是整数。通过首先从初始最小二乘估计中计算噪声方差来调用估计方法,然后将其用于加权最小二乘估计器的成本函数。结果表明,估计结果的准确性要优于无方差加权的估计,例如最小二乘估计器所产生的估计。

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