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A special least squares method for curve fitting

机译:用于曲线拟合的特别最小二乘法

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摘要

A special least squares (SLS) method is proposed which is based on minimizing the sum of squared relative deviations. The author analyzes the problem of classical least squares (LS) in fitting a static characteristic equation and points out the shortcomings of the LS method under some experimental conditions. It is noted that the proposed SLS method could overcome the shortcomings. The formulas of SLS are given and its mathematical characteristics are analyzed. Under the given conditions, this method is unbiased, consistent, and efficient. An example is given of fitting a static characteristic equation of a potentiometer by using the SLS method. The results show that, under the given experimental conditions, the SLS method is superior to the traditional LS method.
机译:提出了一种特殊的最小二乘(SLS)方法,其基于最小化平方相对偏差的总和。作者分析了拟合静态特征方程的经典最小二乘(LS)的问题,并在一些实验条件下指出LS方法的缺点。值得注意的是,所提出的SLS方法可以克服缺点。给出了SLS的公式,并分析了其数学特征。在给定的条件下,这种方法是无偏见的,一致的,有效的。通过使用SLS方法,给出了拟合电位器的静态特性方程的示例。结果表明,在给定的实验条件下,SLS方法优于传统的LS方法。

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