1) robust biased estimation
抗差有偏估计
1.
Firstly,the observed values are corrected by the robust biased estimation such as robust ridge estimator,which only uses the original observed information before the calculation of the filter.
该方法在滤波之前,利用抗差岭估计等抗差有偏估计得到参数估计值,并修正观测向量,把观测向量中的粗差控制在可接受范围之内,然后在滤波中利用自适应因子消除动力学模型误差的影响,这样分两步分别对观测模型误差和动力学模型误差进行控制。
2) bias estimation
偏差估计
1.
Research on joint data association and bias estimation method in radar networks;
雷达组网中联合数据关联与偏差估计方法研究
2.
Taking Earth Centered Earth Fixed(ECEF) coordinate as common grid,this paper discusses bias estimation in 3-D sensor network according to the superposition of the same target in different sensors,the linearized measurement equation of range,range gain,azimuth and elevation deviation of each sensor can be derived via the first order Taylor series expansion.
采用地心地固坐标系作为统一坐标系,研究了3-D传感器组网中的偏差估计问题,根据同一目标位置在各个传感器探测中的迭合条件,运用一阶泰勒展式推导出各个传感器的距离、距离增益、方位角、仰角偏差的线性化公式,利用最小二乘法在线估计出各个偏差量,并实时进行修正,仿真结果验证上述方法的有效性。
3) estimation bias
估计偏差
1.
The solution error and the Kalman filter estimation bias are simulated respectively using the given transfer alignment model for two cases,i.
对于给定的传递对准的误差模型,针对常值外观测速度、位置误差和随机外观测速、位置度误差两种情况,分别对惯导系统的传递对准误差模型的解算偏差和KALMAN滤波器的估计偏差进行了仿真分析。
4) biased estimation
有偏估计
1.
Study on the Restricted Biased Estimation in the Linear Model;
线性模型中的约束型有偏估计的研究
2.
iscusses the problem of linear biased estimation of the parent mean.
本文讨论母体均值的线性有偏估计问题,给出了在均方误差意义下线性有偏估计优于样本均值的充要条件。
3.
To linear regression models Y=Xβ+ε,E(ε)=0,Cov(ε)=σ2V,V>0,the necessary and sufficient condition that biased estimation β*h=(XTV-1X+hI)-1(XTV-1Y+β*) is an admissible estimation is obtained and β*h condition that is superior to ridge estimation is also given.
对于线性回归模型Y=Xβ+,εE(ε)=0,Cov(ε)=σ2V,V>0,给出了回归系数的有偏估计βh*=(XTV-1X+hI)-1(XTV-1Y+β*)(h>0)优于岭估计的条件以及在二次损失下可容许的充要条件。
5) biased estimate
有偏估计
1.
A class of biased estimate of regression coefficients;
回归系数的一种有偏估计
2.
A new class of biased estimate in the multiple linear model;
多元线性模型参数的有偏估计
3.
In the linear regression model:Y=Xβ+ε,E(s)=0,cov(ε)=σ2v,v>0,reference [1] presented a biased estimate:β*s=(XTV-1X+sI)-1(XTV-1Y+β*),where s>0 was a parameter and β was the generalized least squares estimate.
对于线性回归模型:Y=Xβ+,εE(s)=0,cov(ε)=σ2v,v>0,文献[1]给出了有偏估计sβ*=(XTV-1X+sI)-1(XTV-1Y+β*),其中s>0为参数,β表示线性回归模型的广义最小二乘估计,文献[2]中已经证明了sβ*的可容许性并且有很多优良性质。
6) biased estimator
有偏估计
1.
For the linear model with aggregated data,this paper proposed two kinds of biased estimators which have some superiority to the unbiased estimators in the sense of mean square error.
对于聚集数据的线性模型,提出了二种有偏估计,在均方误差(MSE)意义下,讨论了它们的优良性质,并将这二种估计进行了比较。
2.
1),an improved biased estimator is proposed in this paper.
对于半相依回归系统(1)的参数提出一种新的有偏估计,并研究这种估计量在均方误差意义下的优良性质和线性可容许性。
3.
In this paper,a new biased estimator-double k type ridge estimator(DKRE) is proposed to improve some existing biased estimators based on the peculiarity of ill-conditioning of the design matrix.
针对GPS快速定位中设计阵病态性的特点,文中对现有的有偏估计进行了改进,提出了一种新的有偏估计———双k型岭估计。
补充资料:逼近函数的偏差
逼近函数的偏差
deviation of an approxmating function
通近函数的偏差【山血位扣of ana即.油加tiI犯如‘丘.;yoo.e。。e np:6二:狱a沁川e‘中y。二明。。1 逼近函数g〔K和一个给定函数f任叨之间的距离p匆,f).在同一个类叨内可以考虑用不同度量p,譬如一致度量 p(g,f)一碧笃}g(x)一f(x)I,以及积分度量 /(。,,)一(i一(·)一,(·):“·)’‘’,p一和别的度量.至于逼近函数的类K则可以用代数多项式、三角多项式,还有f关于某个正交系的正交展开的部分和,这些部分和的线性平均,以及一些别的集之、
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参考词条