multivariate normal distribution meaning in English

多变量常态分布
多元正态分布

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Of course , it is often effective to apply conventional multivariate statistical process control ( mspc ) to the process whose process variables are subjected ( or approximatively subjected ) to multivariate normal distribution
本文的研究正是着眼于克服这两大假设条件，使过程监控技术能更好地适用于实际工业生产过程而进行的。
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。
Moreover , pca and bsa with their application in process monitoring are simple described 2 ) due to the fact that process information is n ' t always subjected to multivariate normal distribution , a process monitoring method based on pca with support vector classifier is provided , which improves the monitoring performance
此外，还简要地描述了主元分析方法和盲源信号分析方法及它们在过程监控中的应用。 2 )由于过程信息并非均服从正态分布，提出了一种基于支持向量分类器主元分析方法的过程监控方法，仿真表明提高了过程监控的性能。
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。
The results of process monitoring indicate that this method is more effective than the process monitoring method based on conventional blind source signal separation . 6 ) due to the complexity of process information , a process monitoring method which applies independent component analysis and principal component analysis to extract nonnormal distributed process features and normal distributed process features is presented , which avoids the assumption that process information is subjected to multivariate normal distribution
8 )鉴于在过程中，过程信息的平稳性并不确定，提出了一种不考虑过程平稳性能的过程监控方法，仿真表明该方法比基于传统ica的过程监控方法具有更少的误报率和漏报率，而比基于mspc的过程监控方法具有更少的误报率，从而说明该方法的有效性。

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multivariate normal distribution meaning in English

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