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- minimum risk equivariant estimator 最小风险同变估计
- At the same time,we also find out the optimal estimators in the class of Location-Scale linear equivariant estimators. 同时也讨论了位置-刻度线性同变估计中的最优估计.
- An estimator is a random variable. 估计量是一个随机变量。
- The estimator can take various specific forms. 这种估计式可采用不同的具体形式。
- equivariant estimate 同变估计
- Comparison of M-estimator and LTS Estimator in Regression. LTS回归与M估计稳健性的比较。
- Is it possible for an estimator to be unbiased but inconsistent? 是否有可能(一个估计量)是无偏却不一致的?
- The performance of DOA estimator is studied via Monte Carlo simulations. 仿真结果验证了该方法的有效性。
- We are discussing whether OLS estimator satisfy asymptotic normality. 我们讨论是否OLS估计量满足渐近正态性。
- For a small cover over a polytope, its equivariant cobordism class is determined by the tangential representation set. 摘要多面体上的小覆盖的等变配边类是由它的切表示集所决定的。
- So that, in RX needs a well estimator to reconstruct original signal. 因此，在接收端需要有一个良好的估测系统来还原信号。
- We first prove the theorem on equivariant embedding of symmetric spaces in Lie groups. 首先，我们证明对称空间到李群的等变嵌入定理。
- Objective The collinearity in data can produce inaccurate estimator and test. 目的共线关系可产生不准确的估计及检验。
- The condition for a 3D polynomial map to be equivariant is theoretically analyzed and proved. 本指南中的内容将有助于您编写出更好的图形应用程序。
- The unfolding of equivariant bifurcation problems with parameter symmetry under a subgroup of left-right equivalence group is discussed. 讨论分歧参数带有对称性的等变分歧问题在左右等价群的一个子群下的开折,分别给出了其开折是平凡和通用的充要条件。
- Applying a property of orbit structures of twisted conjugate actions to involutions, we then get the aforementioned equivariant embedding of symmetric spaces in Lie groups. 利用本文中证明的李群扭共轭作用的轨道性质，将扭共轭作用中的自同构取为对合自同构，我们就得到了如上所述的对称空间在李群中的等变嵌入。
- The estimator is simple in construction and the error of stator resistance is small. 该辨识器结构简单,辨识的定子电阻误差较小。
- The state variables of such an equivariant bifurcation problem are divided into two groups, in which the first can vary independently, while the other depends on the the first. 将这种等变分歧问题的状态变量分为两组，其中一组的诸状态变量可以独立地变化，而属于另一组的诸状态变量在变化过程中依赖于前一组中的诸状态变量。
- Simulation results show that the ML estimator produces more efficient than the LS estimator. 仿真结果表明，对于此类误差最大似然估计比最小二乘估计有效性更好。
- The result calculated by the Needs Estimator is only a guide based on your information. 根据您提供的资料所计算的结果仅作参考。
