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1)  data smooth processing
数据光滑
2)  Data smoothing
数据平滑
1.
The noise in point cloud data acquired through measuring in reverse engineering has to be eliminated through data smoothing.
逆向工程中测量获得的点云数据中存在一定的噪声点,必须对其进行数据平滑处理。
2.
The paper presents the multi-variable least square method to determine the optimal factor of data smoothing and its amplitude-frequency characteristics and compares it with the general filter.
本文提出了一种利用多变量最小二乘法确定最佳数据平滑因子的方法,建立了优化平滑器特性的数学模型。
3.
This paper presents a new method of experimental strain analysis for plastic deformations based on the theory of data smoothing.
根据数据平滑理论,提出了一种塑性变形实验应变分析的方法。
3)  data smooth
数据平滑
4)  smoothed data
平滑数据
5)  smooth function
光滑函数
1.
The original signals with paper defects are convoluted with the smooth function firstly, then some signals are selected which both preserve the singularity of paper defects and weaken small signal fluctuations .
首先使用光滑函数与纸病信号进行卷积运算 ,然后选取能够保留纸病奇异性特征且同时削弱随机纹理所产生起伏的适当尺度下的信号 ,并对其实施进一步小波变换 ,去除大部分纹理起伏所对应的极大值线 ,最后利用极大值线与纵轴相交的截距来判断纸病。
2.
For the its,the Cauchy s mean value theorem that involves two smooth functions is extended to involving n smooth functions by,and thus obtaining differential mean value.
为拓展它的应用范围,利用相同的手法,将涉及两个光滑函数的柯西微分中值定理推广到了n个光滑函数的情形,得到另一种推广的微分中值公式。
3.
From the formula,the Abstract and concrete known integral formulas of a lot of smooth function in bounded domains can be obtained.
应用单位分解的方法及积分表示中核函数的构造理论,得到Cn空间中有界域上光滑函数的一个抽象积分公式。
6)  smoothing parameter
光滑参数
1.
In according to the Bayesian explanation of the smoothing spline regression, the smoothing parameter l is regarded as the hyperparameter of the stratified Bayesian method.
从光滑样条回归的贝叶斯解释出发,将光滑参数l 看作先验分布中的超参数。
2.
One primary approach to estimate the parameter and nonparametric part is the method of penalized least squares method,generalized cross-validation(GCV)approach is a popular method for selecting the smoothing parameters.
对于这种估计方法,广义交叉验证法提供了一种确定光滑参数的方法。
3.
Then they studied the choice of smoothing parameters both in the regression function and error density.
运用泰勒展式讨论了非参数回归模型中未知误差分布函数f(e)的核密度估计^fn(e)的渐进性质,以及估计量^fn(e)中光滑参数的选择,并给出了f(e)的置信区间。
补充资料:数据通信网(见数据通信)


数据通信网(见数据通信)
data communication network

  shu)u tongxinwang数据通信网(datac。mmunicati。nne饰ork)见数据通信。
  
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