主向量

Methods Firstly, 2-D matrix X with each ECG-cycle as a column vector was constructed. Secondly, the principal components of X based on Karhunen-Loeve Transform were gotten to reconstruct X from the first eigenvector of XXT.

首先以逐拍心电波形为列矢量构造二维矩阵X，再通过KL变换得到X的主分量，然后由X的最大特征向量重构X。

Traditional multivariable analysis method, for example, principal component analysis method and factor analysis method, are common in calculating the mean vector, the covariance matrix of sample and other variables.

摘要传统的多元统计分析方法，如主成分分析方法和因子分析方法等的共同点是计算样本的均值向量和协方差矩阵，并在这两者的基础上计算其他统计量。

It is based on the discrete model of finite analysis to get curvature ,normal vector, direction and geodesic curve,then to analyze and design the structure.

基于有限元分析的离散模型，将离散微分几何领域的最新成果运用于膜结构设计，求解曲面曲率，法向量，主方向及测地线，进行结构分析设计。

Triangular mesh, normal vector, principal curvature, gaussian curvature, mean curvature

三角网格，法向量，主曲率，高斯曲率，平均曲率

The shape-form analysis and load analysis were done by nonlinear FEM. On the basis of surface FEM grid nodes, geometry property research of structure curved surface was progressed, including normal vector, GAUSS curvature, mean curvature and principal direction vector. In this process, the approximate expression of surface didn't need to he known.

采用非线性有限元法进行了膜结构的形态分析和荷载分析，得到了曲面有限元网格；通过离散微分几何方法，研究了薄膜结构曲面的几何性质，包括曲面的法线向量、高斯曲率、平均曲率和主方向矢量，避免了复杂的曲面拟合过程。

EOF, EOF procedures, principal component analysis procedure, suitable for vector field orthogonal decomposition.

经验正交函数，EOF程序，主成分分析程序，适合做向量场的正交分解。

Based on the research work of basic theories including phase space reconstruction,embedding theorem,correlation dimension,local dynamics,Lyapunov exponents,surrogate data etc,based on the research work of general methods such as principal component analysis,correlation dimension GP algorithm,false neighbors method,nonlinear time series prediction,local prediction, adaptive prediction,neural network model,support vector machines regression model, prediction power,nonlinear detection,coarse-graining methodology,conditional entropy and so on,the framework of nonlinear time series analysis are constructed.

在对包括相空间重构、嵌入定理、关联维数、局部动力学、Lyapunov指数、替代数据(来源：A97BC论文网www.abclunwen.com)、等基本理论与其物理意义的研究和讨论基础上；在对包括主分量分析、关联维数GP算法、伪邻近点法、非线性时间序列预测、局域预测、自适应预测、神经网络模型、支持向量回归模型、预测效果、非线性检测、粗粒化方法、条件熵等非线性时间序列一般分析方法的原理和算法研究基础上；构建了新的非线性时间序列分析的理论体系，归纳总结了非线性时间序列分析的基本问题和主要研究方面。2。

This code is the main element analysis codes, which are used to calculate eigenvalues null eigenvector methods.

这个代码是主元素分析的代码，里面有使用MKL计算特征值特征向量的方法。

Then we study holomorphic vector bundles with trivial pull-back on nonprimary Hopf manifolds, of which the fundamental group is 〓, get the filtrable property and the Structure Theorem.

然后我们研究了具有Abel基本群〓的非主Hopf流形上具有平凡拉回的全纯向量丛E，得到其可滤性以及结构定理。

In the method the discrete cosine transform DCT is first applied to noisy facial images to remove its high frequency component noise, the removed noisy face images can be obtain through performing inverse discrete cosine transform. Then the two dimensional principal component analysis (2DPCA) is exploited to the removed noisy face images to obtain a set of eigenvectors that have larger correspondent eigenvalues, and the features of images with lower information dimensions are extracted to get fast recognition speed.

这方法首先对具杂讯脸部影像进行离散余弦转换去除高频杂讯，取得低频影像以降低高频杂讯干扰，然后再对低频影像以二维主分量分析(2DPCA)撷取前几个较高特徵值所对应的一组特徵向量，以降维与资讯集中达到快速辨识的目的。

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。