然后引入新息重组序列解决该最小方差估计问题。这是在网上找到的，…
Then, the latter one is solved by introducing a re-organization innovation sequence.
当噪声的方差已知，且过程是平稳的，应用递推最小方差估计，能够增强信号。
When the noise variance is known, and it's process is stationary, the signal can be enhanced by use of the recursive least mean-square estimation.
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。
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.
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。
The discussion on the property comparison between optimally weighted LS estimate and linear unbiased minimum variance estimate for a linear model is presented.
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。
In the sense of linear unbiased minimum variance estimation, a global optimal recursive state estimation algorithm for this discretized linear system is proposed.
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。
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。
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.
在这种情况下，最优加权最小二乘估计变成关于观测和输入的非线性估计，且与线性最小方差估计不可比。
In this case optimally weighted LS estimate is not a linear estimate of a parameter given input and observation anymore and can not be compared with linear minimum variance estimate.
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)。
A new CFAR detector (UMVEM-CFAR) based on Unbiased Minimum-variance Estimation (UMVE) is presented in this paper.
在信号处理、控制和通讯等技术领域，常常使用线性最小方差估计和最优加权最小二乘估计对参数作出估计。
Linear minimum variance estimate and optimally weighted LS estimate are often used in many fields such as signal processing, control and communications.
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)。
False Alarm Rate (CFAR) detector (FUCAP) based on Fuzzy logic, Unbiased Minimum-Variance Estimation (UMVE) and Cell Averaging (CA) is presented in this paper.
第一种方法，可以使用数值搜索过程设定不同的m和b值并对它们求值，最终决定产生最小方差的估计值。
First, you can use a numerical search procedure to propose and evaluate different values of m and b, ultimately settling on estimates producing the least squared error.
使用最小方差法来确定最吻合的直线涉及寻找使预测方差最小的m和b的估计值。
Using a least-squared-error criterion to determine the line of best fit involves finding estimates of m and b that minimize the squared error of prediction.
可以用两种基本方法来找到满足最小方差法的估计值m和b。
The estimators, m and b, that satisfy the least-squared-error criterion can be found in two basic ways.
卡尔曼滤波是一种线性最小方差状态估计，把它有效地结合阵列天线与多用户检测。
Kalman filter is a linear minimum variance state estimator, and it combined array antenna and multiuser detection effectively.
文中给出了一致最小方差无偏估计(UMVU估计)。
The uniformly minimum varia-nce unbiased estimate (UMVU estimate) of hitting probability has been given.
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。
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.
研究利用导向最小方差(stmv)法实现了宽带相干信号的一维和二维高分辨DOA估计。
The STMV (STeered Minimum Variance) is investigated to realize high resolution 1-d and 2-d DOA estimation for broadband correlated signal.
在此基础上，建立了最小方差损失函数，并结合高斯·牛顿预测误差方法，提出了稳定的，高性能的，在线的复频率直接估计算法。
A cost function is presented, and by applying Gaussian-Newton type recursive prediction error based method, a stable and efficient online frequency estimation algorithm is derived.
对重型商用车声源识别结果说明，利用最小方差无畸变响应估计能较常规波束成形更好地识别出噪声源。
Comparing the results between common beam forming and MVDR method, it shows MVDR method has higher resolution and can identify the complex noise distribution of the moving heavy d.
提出一种最小方差谱估计和最小加权范数约束结合的非参数类数据外推方法。
The paper proposes a nonparameter data extrapolation method based on minimum variance spectrum estimation and minimum weighted norm constraint.
提出一种最小方差谱估计和最小加权范数约束结合的非参数类数据外推方法。
The paper proposes a nonparameter data extrapolation method based on minimum variance spectrum estimation and minimum weighted norm constraint.
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