对一个非球面反射镜进行了实测并对测量结果进行插值运算，进而拟合出零件面形的曲线方程。
An aspherical reflector is tested and testing data are processed by the interpolation calculation, then the curve equation of the component surface shape is fitted.
分别在单序列时建立递进灰拟合模型，在多维数据集时利用属性相关性，对插值结果进行学习优化。
An optimization method for reasoning results is presented, such as recursive grey fitting model for single sequence and attribute correlativity model for multi-dimension data.
从提升格式的应用来说，数据的拟合曲线比数据的插值曲线更能代表数据包络线的低频成分。
From the view of application of Lifting Scheme, the fitting curve can contain more low frequency components of a specific data's contour than the interpolating curve.
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