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When adopting stochastic software in the solution of base line, it can only obtain the covcariance matrix of a single base line vector .

在基线解算采用随机软件时,仅能获得单一基线向量的协方差阵。

In this thesis,using the Bernstein polynomial approximation,Stieltjes transform method and the central limit theorem of martingale,under suitable moment conditions,we prove the CLT of LSS G_n with a generalized regular class C4 of the kernel functions for large dimensional sample covariance matrices.

在适当的矩条件下,当核函数f属于C4时,我们证明了大维随机协方差矩阵的线性谱统计量的中心极限定理。

In this paper we discuss the influence problem of Ridge Estimator in general linear regression model, study the influence analysis on Ridge Estimator with covariance matrix disturbance and data deletion, define Cook distance of Rideg Estimator based on biased estimator.

讨论一般线性回归模型岭估计的影响+分析问题,研究了协方差阵扰动和数据删除对岭估计的影响,给出了岭估计基于有偏估计的Cook距离。

New parameter estimation Markov recursive algorithm for continuous stochastic linear system and bilinear system is proposed.

基于小波变换的连续随机线性和双线性系统参数辨识Markov方法分析研究了连续维纳过程在小波变换下的统计特性,给出了维纳过程的离散小波变换系数所构成的离散随机过程的协方差矩阵计算和估计方法,基此提出了线性和双线性连续随机系统参数辨识的Markov估计方法及其递推算法。

Parameter identification Markov method for continuous stochastic linear system and bilinear system via wavelet transform The statistical properties of continuous Wiener process are studied.

基于小波变换的离散随机线性和双线性系统参数辨识Markov方法分析了由白噪声驱动的有理滤波器输出随机信号在小波变换下的滤波和去相关特性,提出一种在线估计噪声协方差矩阵及其Cholesky分解因子的方法。

A new non-linear quadratic programming Bayesian prestack three-terms inversion method is developed; Firstly, this method is based on Bayesian parameter estimation theory, Gaussian distribution is used for likelihood function and modified Cauchy distribution is used for prior distribution; Secondly, covariance matrix is used to describe the degree of correlation between the parameters; rock physics relations are used to constrain the inversion results; at last, this method is transformed into non-linear quadratic programming problem, and inversion results are acquired under several constraints.

本文提出了一种基于非线性二次规划的叠前三参数反演方法。首先基于贝叶斯参数估计理论,假设似然函数服从高斯分布,并使待反演的参数服从于改进的Cauchy分布,从而提高了反演结果的分辨率;其次用协方差矩阵来描述参数间的相关程度,进一步提高了反演结果的稳定性;最后将问题转化为一个非线性二次规划的求解问题,并在多种约束下得到问题的解。

In order to examine the precision of estimated auto-regressive coefficients, the covariance expression of the estimated auto-regressive coefficients is established using central limit theorem.

为考察AR系数估计的精度,利用中心极限定理建立了估计的自回归系数矩阵协方差的表达式。

In order to examine the precision of estimated auto-regressive coefficients,the covariance exprcssion of the estimated auto-regressive coefficients is established using central limit theorem.

为考察AR系数估计的精度,利用中心极限定理建立了估计的自回归系数矩阵协方差的表达式。

The paper consists of three parts. First, we give the calculation for every order central moment for the Logistic population, mean vector and covariance matrix of the order statistic of random sample from the Logistic population, and means of several special functions for the order statistic of random sample from the Logistic population. Secondly, we discuss the parameter estimation for the Logistic population. Finally, we solve the question about the goodness-of -fit test for the Logistic population.

研究的主要内容分三部分:第一部分是关于Logistic总体各阶中心矩、样本次序统计量期望向量与协方差阵及若干个特殊的样本次序统计量函数期望的计算问题;第二部分是关于Logistic总体分布参数的估计问题;第三部分是关于Logistic总体的拟合优度检验问题。

After orthostatic maneuver, the coefficient of component variance for Low-frequency component increased in healthy control subjects and patients with hypertension, decreased in hypertensive patients with SAS.

对于各频谱段变异系数在调整血压因素后协方差结果显示,与正常对照组相比,休息时SAS合并高血压组总频谱变异系数明显下降(p<0.05),高频段变异系数各组间无差别,与正常对照组和单纯高血压组相比,低频段变异系数明显增加(p<0.01,p<0.01)。

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