查询词典 two sample problem

The traditional Canonical Correlation Analysis based image recognition methods always encounter the Small Sample Size problem,which is due to the size of sample and less than the dimension of sample.In order to solve this problem,a new supervised learning method called Two-Dimensional CCA（2DCCA） is developed.

针对传统典型相关分析（Canonical Correlation Analysis，CCA）的图像识别中出现的小样本（Small Sample Size，SSS）问题，提出二维典型相关分析（Two-Dimensional CCA，2DCCA）。

Meanwhile, it could be seen that there does not exist a confidence interval with width less than 0.5 because of the property of Poisson distribution. Based on these conditions, the author mainly carried out research into two aspects of this problem as follows. Firstly, by numerical and theoretical analysis, the author compares some existent confidence intervals, for example,"exact" confidence interval, Wald confidence interval and Bayesian confidence interval, and finds some deficiencies points of the confidence intervals, whose modification version has been proposed .Also, several better confidence intervals such asare also presented .Secondly, for given confidence coefficient and interval width, the author constructs a class of asymptotical two-stage interval estimate procedures. At the same time, under varies restriction of confidence coefflcientent interval width, the optional sample size of the first stage has been computed by numerical computation. The numerical computation shows that the method considered in this dissertation have good properties and applied value.

同时，由于Poisson分布的特性，我们知道不存在其参数区间长度小于0.5的置信区间，基于这些情况，我们主要展开了以下两个方面的研究：一是利用数值计算分析与理论分析的方法对现有的若干置信区间如"精确"置信区间，Wald置信区间，Bayes置信区间等进行分析比较，发现了一些缺陷，针对这些缺陷，我们进行适当的修正，并得到几种性质较好的置信区间如：修正大样本区间Jeffreys原则下置信区间二是针对已给定的置信系数与区间长度，我们提出了一种渐近的两阶段区间估计程序，并利用数值计算的方法，在各种置信系数与区间长度限定下，算出了最优的第一阶段观测次数，大量数据表明，本文考虑的方法性态良好，具有应用价值。

Jing(1995) extended the EL method to the two sample mean problem for scalar observations and pointed out that it is still Bartlett correctable.

Jing(1995)把经验似然方法推广到标量观察值的两样本均值问题，并指出它仍是可Bartlett修正的。

The main work of this thesis is simulation study on the basis of large sample properties for two estimates by Monte Carlo method with some models. We consider the problem of the choice of window width, consistent rate and some doubtful points about consistent rate with fixed sample size.

本文的主要工作是依据大样本性质，对特定模型的这两种估计用Monte Carlo方法进行了模拟试验，讨论了长度有限的样本情况下窗宽的选择问题，比较了两种估计的拟合程度，相合速度并提出了对相合速度的一些疑难点。

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。

As a result, it is convenient for the recognition system to use the simple linear classifier to segment the sample space, so that the accuracy and distortion invariant ability can be easily achieved. The classification structure of a bifurcating tree is utilized to decompose the classification problem of multi-classes to the multi-stage classification of two classes, which simplifies the design of the classifier, and improves the searching efficiency as well. A gray-scale analysis based method for extracting features from optical correlation result is proposed.

提出了二叉树鉴别分类方法，在使用同类图象的多个典型畸变样本训练识别系统的基础上，利用鉴别分析方法优化各类图象的特征向量在样本空间中的分布，不仅有利于同时提高系统的准确性和抗畸变能力，而且便于采用简单的线性分类器来划分样本空间；利用二叉树分类结构，将多类样本的分类问题分解为多级二类样本的分类问题，不仅简化了分类器的设计，而且提高了搜索效率。

And Pharaoh spoke to Joseph, saying, Your father and your brothers have come to you.

47：5 法老对约瑟说，你父亲和你弟兄们到你这里来了。

Additionally, the approximate flattening of surface strip using lines linking midpoints on perpendicular lines between geodesic curves and the unconditional extreme value method are discussed.

提出了用测地线方程、曲面上两点间短程线来计算膜结构曲面测地线的方法，同时，采用测地线间垂线的中点连线和用无约束极值法进行空间条状曲面近似展开的分析。