1) Unbiased and least variance
无偏最小方差
2) UMVE
无偏最小方差估计
1.
A logarithm detector based on Unbiased Minimum-variance(UMVE) is presented.
利用无偏最小方差估计(UMVE)算法分析了UMVE对数单元平均恒虚警检测器的性能。
2.
A new CFAR detector(UMVEM-CFAR) based on Unbiased Minimum-variance Estimation(UMVE) is presented in this paper.
基于无偏最小方差估计(UMVE)算法,提出了一种新的恒虚警检测器(UMVEM-CFAR)。
3.
False Alarm Rate(CFAR) detector(FUCAP) based on Fuzzy logic,Unbiased Minimum-Variance Estimation(UMVE) and Cell Averaging(CA) is presented in this paper.
基于模糊逻辑,无偏最小方差估计(UMVE)和单元平均(CA)提出一种新的恒虚警检测器(FUCAP)。
3) UMVUE
一致最小方差无偏估计
1.
Judgement and Solution Methods of UMVUE;
一致最小方差无偏估计的判定及其求法
2.
The maximum likelihood estimate and uniformly minimal variance unbiased estimate (UMVUE) of MTTF were made on the one-unit system whose lifetime was assumed to be on GAMMA distribution.
讨论寿命服从单参数GAMMA分布单元平均寿命的极大似然估计和一致最小方差无偏估计;应用BASU定理求出了单元可靠度及串联系统可靠度的一致最小方差无偏估计。
3.
In this paper,they were obtained,the MLE,UMVUE and Bayesiun estimate of N .
设随机变量Ｘ服从１，２，…，Ｎ上的均匀分布，（Ｘ１，Ｘ２，…，Ｘｎ）为来自Ｘ的一组简单随机样本，推导出了Ｎ的极大似然估计、一致最小方差无偏估计及Ｂａｙｅｓ估计，并在极大似然估计的基础上给出了Ｎ的区间估计及检验统计量，最后通过一个实例说明了上述方法的应用。
4) minimum variance unbiased estimation
最小方差无偏估计
1.
In this paper, minimum variance unbiased estimation and lower confidence limits of the structure reliability P r(Y n>a 1Y 1+.
在Y1 ,… ,Yn- 1 ,Yn 相互独立且服从威布尔分布情况下得到结构可靠度Pr(Yn >a1 Y1 +… +an- 1 Yn - 1 )的最小方差无偏估计及其置信下
2.
WT5BZ]Discusses estimation of minimum value I form composite non-homogeneous Poisson process model,and obtains its structural reliability and minimum variance unbiased estimation.
讨论强度随机变量 X服从极小值 型分布 ,应力 { Y( t) ,t∈ [0 ,T]}为复合非时齐 Poisson过程模型的估计问题 ,得到该模型的结构可靠度及其最小方差无偏估计 ( MVUE
3.
The minimum variance unbiased estimation and lower confidence limits of the reliability P=P_r(y_z>α_1y_1+…+α_(n-1)y_(n-1)) are obtained, where y_1,…,y_(n-1), y_(?) are all independent and logarithmic normal variables, α_1,…, α_(n-1) are all known constants.
本文给出y_1,…,y_(n-1),y_n服从对数正态分布时可靠度P=P_r(y_n>a_1y_1+…+a_(n-1)y(n-1))的最小方差无偏估计及置信下限。
5) linear unbiased minimum variance estimation
线性无偏最小方差估计
1.
Based on the linear unbiased minimum variance estimation theory, an asynchronous fusion algorithm that fused the state vector of linear system with arbitrary correlated noises is developed.
基于线性无偏最小方差估计理论,提出了一种任意相关噪声线性系统异步状态向量融合算法。
2.
Based on linear unbiased minimum variance estimation theory, a fusion algorithm which fused the state vector of nonlinear systems with dissimilar sensors with arbitrary correlated noises is developed.
基于线性无偏最小方差估计理论,提出了一种任意相关噪声异类传感器非线性系统状态矢量融合算法。
3.
Based on the forward and backward filtering estimates a smoothing algorithm is developed for linear systems with general correlated measurement noises by using the linear unbiased minimum variance estimation formula.
提出了具有一般相关量测噪声的线性系统的平滑估计算法 ,该算法是在系统正向和逆向滤波估计结果的基础上 ,利用线性无偏最小方差估计获得的 。
6) linear unbiased minimum variance
线性无偏最小方差
1.
The discussion on the performance coparison among least squares estimate, optimally weighted least squares estimate and linear unbiased minimum variance estimate of column singular design matrix for a linear model is presented.
在给定的线性模型下 ,讨论了在设计阵列亏秩时 ,最小二乘估计、最优加权最小二乘估计和线性无偏最小方差估计的性能比较 。
2.
The discussion on the property comparison between optimally weighted LS estimate and linear unbiased minimum variance estimate for a linear model is presented.
在给定的线性模型下 ,讨论了最优加权最小二乘估计与线性无偏最小方差估计性能比较 。
补充资料：最小方差估计
分子式：
CAS号：
性质：在系统模型辨识过程中，寻求使实际测量与计算值间的方差达到最小的参数作为参数的估计值的方法。
CAS号：
性质：在系统模型辨识过程中，寻求使实际测量与计算值间的方差达到最小的参数作为参数的估计值的方法。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
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