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covariance matrix相关的网络例句

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与 covariance matrix 相关的网络例句 [注:此内容来源于网络,仅供参考]

Second,Principal component analysis is essentially a linear method based on the covariance matrix which reflects the linear dependence.

用能反映非线性结构的四阶累积量函数代替相关函数构造矩阵,对主分量分析方法进行改进。

In this paper, a new model adaptation using vector Taylor series is presented, which adapts the mean vector and covariance matrix of hidden Markov model.

该文将矢量泰勒级数用于模型自适应,同时对HMM模型的均值向量和协方差矩阵进行变换,使其与实际环境相匹配。

When oversampling factor is 2, the covariance matrix composed of the coefficients of correlation between those samples can be calculated by numerical method.

按Nyquist采样率均匀抽取出的采样点之间相互独立同分布,推广到过采样系数为2时,得到此时由各采样点之间相关系数构成的协方差矩阵,利用数值计算对其进行分析。

Getting out the Eigen values and eigenvectors of the series covariance matrix by the Jacobi algorithm in C language also is discussed in this paper.

本文使用C语言,利用雅可比算法,编写出可快速求出数据因子分析中所要求的矩阵特征值和特征向量的程序。

MWF holds a new filter structure in which only the cross correlation vectors of each stage instead of the covariance matrix of input series need to be estimated when filtering.

MWF是一种新型的滤波器结构,在滤波时,并不需要知道输入序列的协方差矩阵,只要估计各级的互相关矢量即可。

The commons among those methods is that all of them calculate the mean vector and the covariance matrix of sample then calculate other variables by using them.

这些方法有个共同的地方就是都会计算样本的均值向量和协方差矩阵,并在这两者的基础上计算其他统计量。

This paper focuses on the study of the most popular FAST-MCD method which is improved to overcome its shortcoming, constructs robust mean vector and robust covariance matrix which is applied in PCA method.

本文对目前较流行的FAST-MCD方法的算法进行研究,构造了稳健的均值向量和稳健的协方差矩阵,应用到主成分分析中,并针对其不足之处提出改进方法。

This dissertation focus on the study of the most popular FAST-MCD method which is improved by concentrating on its shortcoming, constructs robust mean vector and robust covariance matrix which is applied in Principal component analysis method and Factor analysis.

本文还著重地对现时最流行的FAST-MCD方法的算法进行研究,构造了稳健的均值向量和稳健的协方差矩阵,应用到主成分分析和因子分析中,并针对其不足之处提出改进方法。

Because Traditional mean vector and covariance matrix are not robust estimator, this dissertation combines ideas of robust statistics with multivariable analysis method from robust statistics aspect.

所以,本文从稳健统计的角度出发,把稳健统计的思想加入到多变量统计分析方法中。

It describes the heteroskedasticity character of interest rate by projecting the sample data onto the EGARCH (1, 1) auxiliary model, makes making the covariance matrix as moment conditions and uses EMM to estimate the parameters. EMM avoids the disadvantage of infeasible or computationally intensive of maximum likelihood functions.

通过将观测数据映射成EGARCH(1, 1)辅助模型描述利率行为的异方差特征,以协方差矩阵为矩条件,用有效矩估计方法得出模型参数,避免了最大似然估计法似然函数不可知或难以求积分的缺陷。

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