全部

1·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。

2·The linear unbiased minimum variance estimate and the optimally weighted least squares estimate are two of the most popular estimation methods for a linear model.

线性无偏最小方差估计与最优加权最小二乘估计是线性模型下两种最常用的估计方法。

3·In the sense of linear unbiased minimum variance estimation, a global optimal recursive state estimation algorithm for this discretized linear system is proposed.

在线性无偏最小方差估计准则下，推导出了该离散化后所得系统的全局最优递推状态估计算法。

4·The estimation of this class of the distributed group can be done by the unbiased estimation, uniformly minimum variance estimation and the optimal linear unbiased estimation.

这一类分布族的参数估计可用无偏估计，一致最小方差无偏估计和最优线性无偏估计。

5·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异类传感器非线性系统状态矢量融合算法。

6·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。

7·FATAFE realizes unbiased estimation and its estimated variance approaches to theoretical lower bound if only signal-to-noise ratio is not very low.

只要信噪比不甚低，频点自跟踪频率估计是无偏的且估计方差接近理论下限。

8·In two-stage estimate, used orthogonal transformation to estimate aggregate average and fitting constants method to estimate variance which was unbiased.

在两步估计法中，利用正交变换得到了总平均的估计，然后采用拟合常数法得到了方差的估计，并证明了该估计是无偏估计。

9·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)。

10·WT5BZ]Discusses estimation of minimum value I form composite non-homogeneous Poisson process model, and obtains its structural reliability and minimum variance unbiased estimation.

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。