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A special least squares method for curve fitting

机译:曲线拟合的特殊最小二乘法

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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:提出了一种基于最小化相对偏差平方和的特殊最小二乘法(SLS)。作者分析了经典最小二乘拟合静态特征方程的问题,并指出了在某些实验条件下LS方法的缺点。注意,所提出的SLS方法可以克服该缺点。给出了SLS的公式,并分析了其数学特征。在给定条件下,该方法是无偏的,一致的和有效的。给出了使用SLS方法拟合电位器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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