多元正态分布 meaning in Chinese
multi dimensional normal distribution
multivariable normal distribution
multivariate normal distribution
Examples
- Lots of research results are obtained in this field , though which are always based on two assumptions : one is that process variables are subjected to multivariate normal distribution ; the other is that samples are subjected to independent and identical distribution ( iid )
在此领域虽已获得了大量成果，但研究基本上是在过程检测数据服从多元正态分布和独立同分布的两个假设下进行的。 - Two primary mathematical tools used in this dissertation are principal component analysis ( pca ) and blind signal analysis ( bsa ) , which are both data - driven methods . pca is not only used as feature extracting method ( where process variables are subjected to multivariate normal distribution ) , but also as a tool for dimension reduction ; bsa is used to extract independent features or process blind source signals from process information in information theory sense , which is more effective than pca in describing the process
主元分析方法不仅作为一种过程特征的提取方法(在过程信息服从多元正态分布的情况下) ，而且也作为一种过程数据降维的主要工具(在过程盲源信号提取的情况下) ；盲源信号分析是从信息论的角度，从过程信息中提取出尽可能独立的过程特征信号或过程原始信源信号，它具有比主元分析更好的刻画过程运行特征的性能。 - It comes up with a new notion , d - solution , which is applied to the distance estimation , by virtue of hilbert space ; furthermore , the dissertation has gained a necessary condition which is identity of minimum mean - square value in linear function classes , so that d - solution extends minimum mean - square value within the domain of nonlinear function equation or equation system ; and , the dissertation studies in detail the classical moment estimation and maximal likelihood estimation on the parameters of ar ( p ) , a series of theorems in the estimation section shows the moment estimators are consistent on the ground of large samples jikewise , those distribution functions of the estimated parameters accord to maximum likelihood estimation converge gauss distribution if the white noise is gaussan
首先，借助hilbert空间理论，提出了距离估计的d -解，给出了d -解的必要条件，这个条件在线性函数类里即是极小二乘估计法， d -解的必要条件满足的方程实质上将极小二乘估计法推广到多函数及非线性函数类。再而，详细地研究了多元弱平稳序列自回归模型ar ( p )的参数经典的矩的替代估计和极大似然估计，获得矩的替代估计的一致性的结果。对基于gauss白噪声假设多元弱平稳序列自回归模型的均值、白噪声的协方差阵的极大似然估计都有依分布收敛到多元正态分布的统计性质。