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This approach not only avoided face information missing, increased the number of composite feature, but also avoided the small sample size problem in theory.

这种方法在避免图像信息的丢失、增加组合特征的同时,理论上也能避免单纯使用线性判别分析进行特征抽取时容易出现的小样本问题

The fourth chapter arises the problem of aging of sample aiming at the applied fixed sample survey.

第四章,针对采用的固定样本调查方法,提出样本老化问题,并由此引出关于样本轮换问题的简单探讨,提出样本轮换主要遵循的原则。

To avoid the SSS problem, a nonsingular within-class scatter matrix is constructed directly using the original two dimensional image matrix, and DLDA method is used to obtaining the feature matrix in this new algorithm.

该算法在克服小样本问题的同时,不会丢失图像中的有用信息,而且可以避免采用奇异值分解导致的无法精确计算特征向量的问题。

To sum up, main results of this study were listed as follows:(1) After analyzing the main factors affecting generalization function of neural network, and aiming at poor representativity of hydrologic time series samples, standardization method of transforming extreme was presented to deal with input sample of time series, which could make the input samples lie in the interpolation range of training samples even if they lie in the extension of training samples, so it improved generalization function of neural network and accelerates network convergence speed.

概括起来,本文取得的主要研究成果如下:(1)对影响神经网络泛化能力的主要原因进行了阐述,针对水文时间序列样本的代表性不好这一问题,提出了采用变最值的规范化方法处理时间序列输入样本,使神经网络的输入样本即使为训练样本的外延,规范化后也处于训练样本的内插范围,从而改善神经网络的泛化能力,并加快网络收敛速度。

The measurement system error model analysis is introduced into power system real time network state analysis as an important part for the first time, which can improve on the state estimation quality and provide the capability to monitor the operation of the measurement system; 2. The theory and algorithm of the on-line estimation and update of measurement noise variance based on the relation between the residual variance and noise variance. The statistic properties of the sample variance are discussed and the relation between the estimation precision and sample size under given confidence level is derived; 3. The theory and algorithm of detection and identification of measurement bias are presented, which is based on the relation between residual mean and noise mean. The statistic properties of sample mean are discussed and the relation between estimation precision and sample size is derived; 4. The Givens orthogonal transformation algorithm is selected to be the essential algorithm of state estimation, the fast orthogonal transformation algorithm with damp factor and the algorithm which can handle the zero injection measurements efficiently are presented; 5. The quantity analysis theory of bad data detectivity and identifibility are presented, which describes the relation between the elements in matrix W〓 and bad data amplitude and can provide the theory base for measurement system design and valuation.

一、首次将量测系统误差模型分析做为一个环节引入电力系统实时网络状态分析中,为EMS系统增加了实时监视系统运行、修正量测系统误差模型的新功能,进一步发挥了实时网络状态分析应用软件的潜力;二、首次提出了应用样本方差在线估计与修正量测系统误差方差的基本理论,讨论了样本方差的统计性质和概率分布,推导出了样本容量、估计精度和置信度之间的关系,给出了在线估计与修正量测系统误差方差的算法;三、首次提出了应用样本均值在线检测与辨识量测偏差的基本理论,讨论了样本均值的统计性质,推导了样本容量、估计精度和置信度之间的基本关系,给出了在线检测与辨识量测偏差的算法;四、在状态估计算法设计中,以Givens变换算法做为基本算法,提出了快速正交变换阻尼因子法和可以有效地处理零注入量测的混合法,并对实时应用中的一些问题进行了讨论;五、提出了不良数据可检测性与可辨识性的定量分析理论,揭示了描述量测系统配置、网络结构与参数的残差灵敏度矩阵中的元素与不良数据的幅值在可检测、可辨识能力上的定量关系,为量测系统配置设计与评价提供了理论基础;六、综合国内外最新研究成果,采用自适应自回归预测技术和稀疏矢量技术,构造了较完善的不良数据检测与辨识算法。

A novel algorithm for solving the small sample size problem in face recognition is proposed.

提出了一种在人脸识别中解决小样本问题的新算法。

Both the theory and practice showed that SVM was not only simple in structure, but possessed preferable popularization, especially in little sample which overstudying was solved in the process of ANN and part minimization was successfully overcame.

理论和实验表明,SVM不但结构简单,而且具有较好的泛化能力,尤其是对于小样本问题,成功地克服了ANN学习过程中的&过学习&和可能会陷入局部极小问题。

Linear Discriminant Analysis is one of the most popular linear projection techniques for feature extraction.

线性判别分析是一种较为普遍的线性特征提取方法,它的主要缺点是在应用时经常遇到小样本问题,同时其准则函数并不与识别率直接相关。

Linear Discriminant Analysis is one of the most popular linear projection techniques for feature extraction. The major drawback of applying LDA is that it often encounters the Small Sample Size problem. Besides, their optimization criteria is not directly related to the classification accuracy.

摘要线性判别分析是一种较为普遍的线性特征提取方法,它的主要缺点是在应用时经常遇到小样本问题,同时其准则函数并不与识别率直接相关。

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。

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然而,正如其名字所指出的那样,CD盘不能写,也不能用任何方式改变其内容。

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