本文提出了一种选主元迭代法。
In this paper, We developed a select main element iterative method.
对主元模型的故障检测能力进行了详细的分析计算。
Fault detection and diagnosis sensitive capacity of PCA model was analyzed and calculated in detail.
然后根据分类数据建立主元模型组来描述整个过程；
The PCM group is established by using the classified data sets to describe the entire process.
如果目标是一个属性引用：引用中的主元表达式被求值。
If the target is an attribute reference: the primary expression in the reference is evaluated.
讨论了基于多尺度主元分析的故障传感器数据重构问题。
Multi-Scale Principal Component Analysis for data reconstruction of the faulty sensor is discussed.
内容涉及模糊分割技术、BP神经网络、主元分析技术。
The content includes in the fuzzy segment, BP neural networks and principal component analysis.
在训练阶段，核-主元分析用来捕捉非线性的手写变化。
In the training phase, kernel principal component analysis is used to capture nonlinear handwriting variations.
为此，提出了基于主元分析法和FRF的井架损伤识别方法。
Therefore, the derrick damage identification method based on principal component analysis and FRF is put forward.
Registry是用于服务交互端点描述的主元数据存储库。
Registry is the master metadata repository for service interaction endpoint descriptions.
论文提出了一种基于改进的自适应主元提取算法的人脸识别方法。
An improved adaptive principal component extraction algorithm based face recognition method is proposed in this paper.
本文提出了一种基于主元分析法（PCA）的多模板字符识别算法。
This paper presented a new multi-template character recognition method based on principal component analysis(PCA).
对于连续生产过程，可以采用普通的主元分析方法进行过程数据分析；
For continuous process, the normal PCA can be used to analyze the process data.
研究了基于高阶谱（主要是三阶谱）和主元分析的故障特征提取方法。
The extracting fault features approach based on high-order spectral for pump valves of reciprocating pump was investigated, especially third order spectral analysis.
尝试性地将基于主元分析的多变量统计方法应用于连铸结晶器过程的监测。
The authors try to use multivariate statistics method based on principal component analysis (PCA) to monitor continuous casting mould process.
多主元高熵合金是一种新型的合金材料，是多种元素处于领导地位的合金。
High entropy alloy is a kind of advanced alloy, which multiple elements are in the leading positions.
提出一种基于人脸肤色统计模型和主元分析(pca)的人脸检测和定位方法。
This paper presents a human face detection and localization approach which is based on skin color detection and principle component analysis (PCA).
提出一种基于核主元分析(KPCA)和多级神经网络集成的汽轮机故障诊断方法。
One new method for fault diagnosis of steam turbine based on kernel principal component analysis (KPCA) and multistage neural network ensemble was proposed.
为此提出了一种多向核主元分析(MKPCA)算法用于间歇过程的建模与在线监测。
A method based on multiway kernel principal component analysis (MKPCA) was proposed to capture the nonlinear characteristics of normal batch processes.
在HSV彩色空间将颜色信息和局部空间特征相结合，利用主元神经网络提取主成分；
Color information and local spatial features are combined in the HSV color space in order to obtain principal components by principal component analysis neural networks.
对多元统计过程控制常用的分析方法进行了介绍和总结，如主元分析、多向主元分析。
Conventional analytical methods used in Multivariate Statistical Process Control, such as Principal Component Analysis, Multi-way Principal Component Analysis are summarized.
该方法由三部分组成：主元分析pca、时间延迟神经网络、软测量模型的在线校正。
It is composed of three elements: PCA, time-delay neural network and model updating, where the offline model is trained through the algorithm GABP.
算法采取对主元进行扰动优化匹配的方法检测人脸，本文称此方法为全局最优的方法。
When detecting a face, we adopt the method of disturbing principle components of model to match special facial image, which is called whole optimization method in this thesis.
本文提出了一种选主元迭代法。对一类发散的线性系统讨论了其收敛性，并举例说明之。
In this paper, We developed a select main element iterative method. For a class linear system of divergence discussed convergence, and illustrate by examples.
应用基于主元分析的故障诊断方法对浮式油轮生产储油卸油系统进行故障检测与诊断研究。
Used fault diagnosis method based on Principal Components Analysis to research the fault monitoring and diagnosis of Floating Production Storage and Off-loading system.
基于主元分析(pca)的统计检测方法已经被广泛应用于各种化工过程的故障检测和识别。
Numerous statistical process monitoring methods based on principal component analysis (PCA) have been developed and applied to various chemical processes for fault detection and identification.
应用主元分析方法将高维数据转换到低维数据空间，这使得过程监测可以在低维的空间内进行。
High dimension was changed into low dimension by using principal component analysis method, process detecting could be carried out in the low dimension space.
概率主元分析(PPCA)能够根据过程变量的预测误差及其主元的白化值实现对过程的监控。
Probabilistic principal component analysis (PPCA) can realize the process monitoring (according) to the whiten values of process variables' prediction error and their scores.
提出利用主元分析（PCA）和学习矢量量化神经网络（LVQ）相结合的方法进行人脸识别。
This paper proposes a face recognition method based on PCA and LVQ neural networks.
Registry andRepository是用于服务交互端点描述的主元数据存储库。
Registry and repository is the master metadata repository for service interaction endpoint descriptions.
在多变量统计过程控制中，传统的方法主要包括主元分析和偏最小二乘，这些方法存在着诸多缺陷。
Principal component analysis (PCA) and partial least squares (PLS) are the conventional techniques of multivariate statistical process control but exist some defects.
应用推荐