Calibration by an enhanced Full Least Squares method

被引:0
|
作者
D'Antona, Gabriele [1 ]
Rocca, Luca [1 ]
机构
[1] Politecn Milan, Dipartimento Electtrotecn, Pzza Leonardo Vinci 32, I-20133 Milan, Italy
关键词
calibration; curve fitting; data models; least square; parameter estimation; parameter uncertainty; surface fitting;
D O I
10.1109/IMTC.2006.328266
中图分类号
TH7 [仪器、仪表];
学科分类号
0804 ; 080401 ; 081102 ;
摘要
This paper deals with the problem of the regression of measured quantities when measurement uncertainty affects both the regressed quantity and the independent variables. A new criterion is given, based on an enhanced Full Least-Squares (FLS) method The novel approach shares with the FLS similar metrological foundations, but it differs in that the propagation of the measurement uncertainty is performed numerically and not, as in a conventional FLS, on the basis of the classical law for the propagation of uncertainty based on a first order Taylor expansion. An example of application of the novel method is given together with a comparison with the regression obtained by the conventional FLS method.
引用
收藏
页码:965 / +
页数:2
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