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1)  G instrumental transformation
G辅助变量替换
2)  auxiliary transform
辅助变换
1.
This paper put forward two graphic solutions to determine the minimal distance between the line outlet of cable fastened tower and the cable,with the graphic principles of auxiliary transform of graphic geometry,in the design of insulated distribution of high voltage circuits.
提出了在高压送电线路的绝缘配合设计中,用画法几何中辅助变换的作图原理,来确定外拉式塔导线出口处一段与拉线的最小间距的两种图解方法,并用计算方法验证了图解方法的正确
3)  secondary variable
辅助变量
1.
Precision of spatial interpolation for forest duff layer depth based on secondary variable
基于辅助变量的森林半腐层厚度空间插值精度
2.
The selection of secondary variable is crucial in soft sensor.
辅助变量的选择是软测量和推断控制成功与否的关键之一。
3.
The selection of the secondary variable consists in the selection of the type, the number and the detect spot.
辅助变量的选择包括变量类型、数量及检测点的选择,是软测量建模的第一步,直接关系到软测量质量的好坏。
4)  instrumental variable
辅助变量
1.
Proposes an algorithm of bi-iteration subspace tracking using instrumental variable,and it is a bi-iterate rank-one update model.
提出了一种运用辅助变量的双迭代子空间跟踪方法。
2.
Under the assumption that the sources are narrow-band and their temporal correlation is longer than that of noise,a new method to solve this problem is proposed which combines the methods of instrumental variable and unitary transformation.
本文在窄带信号条件下,利用信号的时间相关长度大于噪声的时间相关长度这一事实,提出了一种色噪声环境下基于辅助变量和酉变换的信号源数目估计方法。
3.
As an important identification method,the instrumental variable method can give the unbiased parameter estimation for systems with colored noises and unknown noise models.
辅助变量辨识方法是一类重要的辨识方法,然而对于盲辨识,系统输入未知,辅助矩阵的选择就成了难题。
5)  instrumental variables
辅助变量
1.
Single stationary observer bearings-only tracking using instrumental variables;
使用辅助变量的单静止站纯方位目标跟踪
6)  supplementary variable
辅助变量
1.
Hamiltonization and solution of differential equations by introducing supplementary variables;
微分方程借助辅助变量的Hamilton化与求解
2.
This paper establishes an extended system of a system of differential equations by introducing some supplementary variables.
通过引进辅助变量的方法建立微分方程组的扩充系统。
补充资料:辅助变量法
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性质:是针对最小二乘法的缺陷(比如将系统干扰假设为白色噪声,而实际是有色噪声)提出的一种改进方法,其关键在于如何构造辅助变量矩阵,它能较为有效地处理有色噪声的情形。

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