特征向量

In chapter Ⅰ, a historial review of structure control is given; In chapter Ⅱ, A discussion of the controllability and observablity of flexible structures is given, Two kinds of controllability and observablity index are defined, and applied to actuator allocation; chapter Ⅲ considers the reduction of high order flexible structure mode; the content of chapter Ⅳ is about the basic problem of distributed parameter control system design. It is proved that a stable controllor in mode space may be unstable in real use in distributed paramater systems, also, by closed loop mode concept, a pole assignment method of flexible structure controllor design is given; chapter Ⅴ is about the low-authority controllor design, it is pointed out by use of high order eigenvalue/eigenvector perturbation, a better controllor can be designed; chapter Ⅳ considers flexible structure reduced order control; chapter Ⅶ disscusses the basic problem of flexible structure computer control, analyses discreate controllablity and observablity and its computing, the sample period and coefficient wordlength; chapter Ⅷ is on the problem of low flexibility compensation; chapter Ⅸ is a design example.

在第一章简要回顾了挠性结构控制的历史，并且指出控制中的一些问题；第二章讨论了挠性结构的能控性与能观性，定义了两类能控性程度和能观性程度指标，还将能控性程度概念应用于执行器位置的确定；第三章论述了高阶模型的降价问题，比较了适于挠性结构模型降阶的方法，指出其适用范围；第四章内容是分布参数系统设计的基本问题，首先证明在模态空间中设计的稳定的控制器在实际分布系统上可能是不稳定的，进而根据闭环模态的概念，获得挠性结构控制器设计的极点配置方法；第五章的内容是关于低权控制器的设计问题，指出利用特征值高价摄动和特征向量的摄动，可以设计出更加完善的低权控制器；第六章讨论挠性结构降阶控制问题；第七章讨论挠性结构计算机控制的基本问题，分析了时间离散化模型的能控性和能观性及其计算问题，讨论了采样周期选择和系数字长问题；第八章讨论低挠性结构的补偿问题；第九章的设计例子用来说明第二章和第四章的结果。

Firstly, it introduced the import principium resolving thread and steps of analytic hierarchy process. Secondly, it erected model of population modernization, which based on the steps of analytic hierarchy process. Lastly, it got the maximal eigenvalue of dissymmetric matrix and corresponding eigenvector with SAS, and normalized the eigenvector to get weight value.

本章分为两部分，第一部介绍分析法的提出、原理以及解决问题的思路和步骤；第二部建立模型确定权重，根据层次分析法的原理和步骤，建立人口现代化指标体系的模型，运用SAS求解所构造的非对称判断矩阵的最大特征值，从而得出所对应的特征向量，变形后得到权重。

First, a fixed-dimensional feature vector is generated for each protein sequence using the frequency of the hydropathy blocks occurring in the sequence.

首先，利用蛋白质序列中亲水模块的出现频率，每条蛋白质序列被转换为一个特征向量。

Chapter 8: We discuss the acceleration of multigrid by Krylov subspace approaches, and recognize the reason for slow convergence of algebraic multigrid methods is that error reduction is significantly less efficient for some very specific error components which may cause a few eigenvalues of the algebraic multigrid iteration matrix to be considerably closer to 1 than all the rest. However, the eigenvectors belonging to the few isolated eigenvalues can be expected to be typically captured after only a few conjugate gradient iterations, which accelerate algebraic multigrid algorithms. Theoretical analysis and numerical results of some practical problems show the iterant recombination accelerates algebraic multigrid convergence.

第八章：先介绍用Krylov子空间迭代法加速一般多重网格方法收敛的基本框架，然后紧紧抓住引起代数多重网格方法收敛减慢的根本原因往往是误差减小对几个特别的误差分量不明显，这导致代数多重网格方法的迭代矩阵的几个特征值接近于1，而共轭梯度方法则能比较典型地捕捉属于孤立特征值的特征向量，从而推导出有效的共轭梯度加速算法和程序实现，不仅从一些具体的实际应用例子的数值结果去验证迭代复合加速收敛的效果，而且还从理论上分析了预处理共轭梯度法加速代数多重网格法收敛的机理。

The application of BP nerval network to failure diagnosis of hydraulic systems in construction machinery is studied. Through collection of the system data, derivation of eigenvectors and structure of classifiers, a learning algorithm is established on the basis of network training. Tests show that satisfactory results can be obtained by the nerval network.

将BP神经网络理论应用于工程机械液压系统故障诊断中进行研究，通过系统数据的采集、特征向量的提取和分类器的构造，在对网络进行训练的基础上，建立了学习算法，通过试验可以看出神经网络能给出的满意结果。

This method consists of two steps: first, the image is divided into numbers of nonoverlapping blocks and the GMRF parameters are computed for each of these blocks, then a clustering method is used to merge these blocks, a coarse segmentation and texture types of the image are obtained. Second, a deterministic relaxation neural network is constructed, the parameters of the model estimated from the first step are used as input data, through neural network computation, a fine segmentation is obtained.

提出一种基于高斯-马尔可夫随机场和神经网络的无监督纹理分割方法，方法分为两步：第一步先将图像分为不重叠的小块，在小块中计算GMRF参数，并将此参数和该块的均值、方差作为该块的特征向量，然后进行聚类，得到原图像的一个初始分割和图像中所包含的类别数；第二步构造一个决定性松弛的神经网络，将第一步得到的结果作为初始输入，经过神经网络计算，得到一个精确的分割结果。

At the same time it is know by analysis about matrix characteristic of the similar orthogonally that not only the characteristic value after the transformation is equal to the ones before the transformation and they are independence to time variable of the system, but also the eigenvectors of the formed system can showed the effect of the time variable on original system.

同时，根据矩阵正交相似的性质分析得知：不仅变换前后两个矩阵的特征值完全相同并与时间变量无关，而且时间变量对此系统的影响可以只由变换后系统的特征向量来描述，给出了非典型阻尼振动系统物理意义上的解释。

Following from the results of sensitivity analysis of standard eigenvalue problems,the differentiability of semisimple multiple eigenvalues of nonsymmetric generalized eigenvalue problems is proved,and the derivatives of semisimple multiple eigenvalues and the series expansions of the corresponding eigenvectors are obtained.

以标准特征值问题灵敏度分析的有关结论为基础，证明了单参数非对称广义特征值问题半单重特征值的可微性，给出了特征值导数的表达式和特征向量的级数展开式。以所得结论为基础，定义了广义特征值问题半单重特征值的灵敏度，给出了确定矩阵对中敏感元素的方法

First the power spectrum of fault signals is decomposed by wavelet analysis, which predigests choosing method of fault eigenvectors.

首先对故障信号功率谱进行小波分解，简化了故障特征向量的提取。

By introducing safe-inserted-node and safe-deleted-node concept into the structure,the performance of tree creation is reenforced.

同时，给出了基于该结构的特征向量插入算法。

In the negative and interrogative forms, of course, this is identical to the non-emphatic forms.

。但是，在否定句或疑问句里，这种带有"do"的方法表达的效果却没有什么强调的意思。

Go down on one's knees;kneel down

屈膝跪下。。。下跪祈祷