主向量

Proposed are a method of identifying lithology based on principal component analysis and least square support vector machine.

提出一种基于主成分分析的最小二乘支持向量机的岩性识别预测模型。

Power Extrapolation uses eigenvalues directly in the process of iterating hyperlink-based Markov matrix.

Power Extrapolation算法通过特征值直接求解马尔可夫超链接矩阵的主特征向量，但该算法的迭代次数与参数d的选择密切相关。

The decomposition of the eigenspace of the defective matrix and the general form of Jordan chain ;2. The general form of the maximal Jordan chain s of the defective matrix is getten with the notation of depths of the generalized eigenvectors.

利用广义特征向量的深度，获得极大若当链的一般形式，并推导出在满足PJP-1=SJS-1的2个可逆矩阵P和S之间存在一个主对角线上具有上三角分块Toeplitz子阵的可逆矩阵H，使得S=PH，从而证明广义特征矩阵的唯一性。

The framework established was practical and universal, and could provide abase for specific area to select its assessment indicators. The operable indicatorsystem developed which synthetically reflected the sustainable development status ofliling could fill up the blank of regional sustainable development evaluation in liling,and this work was of practical and strategic significance to a certain extent. Inallusion to the flaw existed indimensionlessness of original data in grey system,mean value method was adopted instead of traditional standardized method, and theguidance for confirming the direction of eigenvector was first brought to grey systemin the application of sustainable development evaluation aimed to increase theobjectivity and accuracy of evaluation. The evaluation results on liling could supplybeneficial references for decision makers to make and adjust sustainabledevelopment strategic goal and counter measures.

本文所构建的区域可持续发展指标体系框架具有实用性和通用性，可作为特定区域在筛选具体评价指标时的参考依据；针对醴陵市建立的区域可持续发展指标体系易于操作，能够综合反映醴陵市可持续发展的各个方面，在很大程度上填补了区域可持续发展评价研究的空白，具有一定的实践意义和战略意义；应用主成分分析法评价各子系统的可持续发展水平时，针对原始数据处理存在的弊端，提出以均值法代替传统的标准法，并首次引入了特征向量确定的原则，从理论上可提高评价的客观性与准确性；对醴陵市区域可持续发展状况的评价结果，可以为醴陵市可持续发展总体战略目标及相关措施的制定与结构调整提供有益参考。

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。

Tests on mean vector, discriminant analysis, multivariate analysis of variance, canonical correlation, principal components, and factor analysis.

多元分析——方法：均值向量检验，判别分析，多元方差分析，典型相关分析，聚类分析，主成分分析，因子分析。

To solve this problem, this paper proposed a new method to reduce the dimensions of the documents and extract the semantic concepts of words using kernel principal component analysis.

利用核主成分分析和支持向量机，提出一种通过约简文本数据维数抽取语义概念、基于语义概念进行文本分类的新方法。

For the algorithm, the kernel primary component model according to the normal system is constructed firstly.

本文提出了基于核主元和多支持向量机分类的过程监控和故障诊断方法。

Scatter matrix ; principal component analysis ; eigenvector ; feature extraction

散布矩阵；主成分分析；本征向量；特征提取

The split between the two groups can hardly be papered over.

这两个团体间的分歧难以掩饰。

This approach not only encourages a greater number of responses, but minimizes the likelihood of stale groupthink.

这种做法不仅鼓励了更多的反应，而且减少跟风的可能性。