例句與造句

1. 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
   本文的研究正是著眼于克服這兩大假設(shè)條件，使過程監(jiān)控技術(shù)能更好地適用于實(shí)際工業(yè)生產(chǎn)過程而進(jìn)行的。
2. 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 )
   在此領(lǐng)域雖已獲得了大量成果，但研究基本上是在過程檢測數(shù)據(jù)服從多元正態(tài)分布和獨(dú)立同分布的兩個(gè)假設(shè)下進(jìn)行的。
3. 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，還簡要地描述了主元分析方法和盲源信號分析方法及它們在過程監(jiān)控中的應(yīng)用。 2 )由于過程信息并非均服從正態(tài)分布，提出了一種基于支持向量分類器主元分析方法的過程監(jiān)控方法，仿真表明提高了過程監(jiān)控的性能。
4. 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
   主元分析方法不僅作為一種過程特征的提取方法(在過程信息服從多元正態(tài)分布的情況下) ，而且也作為一種過程數(shù)據(jù)降維的主要工具(在過程盲源信號提取的情況下) ；盲源信號分析是從信息論的角度，從過程信息中提取出盡可能獨(dú)立的過程特征信號或過程原始信源信號，它具有比主元分析更好的刻畫過程運(yùn)行特征的性能。
5. 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 )鑒于在過程中，過程信息的平穩(wěn)性并不確定，提出了一種不考慮過程平穩(wěn)性能的過程監(jiān)控方法，仿真表明該方法比基于傳統(tǒng)ica的過程監(jiān)控方法具有更少的誤報(bào)率和漏報(bào)率，而比基于mspc的過程監(jiān)控方法具有更少的誤報(bào)率，從而說明該方法的有效性。
6. It's difficult to find multivariate normal distribution in a sentence. 用multivariate normal distribution造句挺難的
7. A . p . verbyla and w . n . venables ( 1988 ) extended the ordinary growth curve model into the extension of growth curve model and obtained an estimate of the unknown parameter matrix under the conditions that the matrix of observations follow multivariate normal distribution , where every design matrix has full column rank [ 7 ]
   A . p . verbyla和w . n . venables ( 1988 )將gc模型進(jìn)行了推廣，得到了推廣增長曲線模型( theextensionofgrowthcurvemodel簡稱egc模型) ，并在觀察矩陣服從正態(tài)分布，各設(shè)計(jì)矩陣均為列滿秩的條件下，給出了參數(shù)矩陣估計(jì)值的一種算法。