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In this paper, the function of regression matrix is estimated in a growth curve model, and the necessary and sufficient conditions that a linear estimator of the function is admissible among the class of all lin ear estimators under matrix loss are obtained.

摘 要:对增长曲线模型中回归矩阵的函数的线性估计进行了研究。在矩阵损失下,作者得到了线性估计在一切线性估计类中可容许的充要条件。

The effects of small angle rotation of texture images and noise to the parameterestimation of Gauss-MRF model are researched.

研究了工件表面纹理图像的小角度旋转和噪声对高斯马尔可夫随机场模型的参数估计的影响,数据分析表明高斯马尔可夫随机场模型所估计的参数对于小角度的旋转纹理具有不变性。

We get the necessary and sufficient conditions about admissibility for linear estimators of estimable function among the inhomogeneous linear class.

利用矩阵的向量化方法,研究了带线性约束的增长曲线模型中可估函数的线性估计在非齐次线性估计类中可容许的充要条件。

The algorithm is featured with insensitivity to Gaussian noise. The proposed algorithm can estimate DOAs without search and match problem.

因此,在阵元数相同的条件下,与传统的循环域DOA估计算法相比,DOA估计的分辨率和可估计源的个数均得到大幅度的提高。

Net realisable value is the estimated selling price in the ordinary course of business, less the estimated cost to completion and estimated selling expenses and related taxes.

可变现净值按日常活动中,以存货的估计售价减去至完工时估计将要发生的成本、估计的销售费用以及相关税费后的金额确定。

It is shown that finally this problem turns to the estimation of the real joint eigenvalues of three real matrices and solve the joint eigenvalue estimation by a recently proposed simultaneous diagonalization algorithm.

通过同时对角化算法估计矩阵的联合特征值,获得了参数联合估计的强可辨识性,即允许信号参数在任何一维任意重复,并可以使估计参数实现自动配对。

And three main steps of all subspace algorithms are explored. First, using an LQ-decomposition, the projection of the row space of specific data Hankel matrices is calculated. Next, the SV-decomposition of the projection is calculated to directly lead to the observability matrices and a Kalman filter estimation of the state sequences.

概括了子空间辨识算法的三个主要运算步骤:首先由LQ分解计算特定Hankel矩阵的行空间投影;再对该投影进行SVD,获取系统的可观测矩阵及状态序列的Kalman滤波器估计;最后由可观测矩阵和/或估计的状态序列确定系统矩阵。

And three main steps of all subspace algorithms are explored. First, using an LQ-decomposition, the projection of the row space of specific data Hankel matrices is calculated. Next, the SV-decomposition of the projection is calculated to directly lead to the observability matrices and a Kalman filter estimation of the state sequences. Last, the system matrices are extracted from the observability matrices and/or the estimated state sequences.

概括了子空间辨识算法的三个主要运算步骤:首先由LQ分解计算特定Hankel矩阵的行空间投影;再对该投影进行SVD,获取系统的可观测矩阵及状态序列的Kalman滤波器估计;最后由可观测矩阵和/或估计的状态序列确定系统矩阵。

In Chapter 2, the Balanced LS Estimation is defined for the linear model when its error covariance is positive definite or singular. The new estimation as well as the necessary and sufficient conditions is gained for its unbiasedness, efficiency and admissibility.

第2章提出了一般线性回归模型和奇异线性回归模型平衡LS估计的概念,得到回归系数β的平衡LS估计,进而探讨了这种估计的无偏性、有效性和可容许性。

The energy loss through feces was 0.077C (C: food consumption, KJ/d) and the energy loss through excretion was 0.052C at maximum feeding rate. In that the ratios of F and U to C were low in fish energy budget equation (Cui et al., 1997), the energy loss through feces at optimum feeding rate could be estimated by 0.077C〓(C〓: the optimum feeding rate) and the energy loss through excretion at optimum feeding rate could be estimated by 0.052C〓. The relationship between total energy content for immature gibel carp and body weight was lnE=1. 476+1. 127lnW.

最大摄食率条件下,异育银鲫排粪能损失:F=0.077C,排泄能损失:U=0.052C;由于排粪能及排泄能在能量收支方程中所占比例不大(崔奕波等,1997),最适摄食率条件下的排粪能损失可估计为F〓=0.077C〓(C〓:最适摄食能,KJ/d),排泄能损失可估计为U〓=0.052C〓;性未成熟异育银鲫的能量含量与体重的关系为:lnE=1.476+1.127lnW

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