鉴别分析

词组短语

discriminatory analysis

与鉴别分析相关的网络例句 [注：此内容来源于网络，仅供参考]

Keywords: Fisher linear discriminant analysis,kernel function,orthogonal complementary space,human face recognition

为了能利用非线性鉴别特征进行人脸识别，提出了一种基于核的子空间鉴别分析方法。

A warning signal from the system which indicates high EC or EC ratio of a dairy cow is used to inform the milker to pay attention to the suspected cow. The detection thresholds of EC and ECR to determine whether a quarter or a dairy cow is infected with mastitis correspond with the criterion of SCC = 500×103 cells/ml for quarter foremilk of a dairy cow. The performance of online system for mastitis detection in dairy cows is evaluated with several methods, such as the detection thresholds, running analysis and discrimination analysis.

以分房乳 SCC 500 × 103 cells/ml 作为乳房炎感染与否的门槛值，由牛旁采样分房乳样的检测与分析，探讨影响牛乳 EC 大小的相关因素及其关系，如分房乳中的氯离子浓度、挤乳时间、挤乳前后及乳成份，利用变异数分析探究未感染与感染乳房炎的分房乳之间，其 EC 及 ECR 物理性质，SCC、乳酸去氢酵素及 pH 化学性质及乳脂率、蛋白质及乳糖等乳成份的差异，进而利用统计鉴别分析探讨 EC 相关参数结合乳成份参数对乳房炎检测的准确度。

objective:study female the yin false wet you of clinical pathology characteristics and discriminate judgment.method:rightness 69example sufferer of clinical and laboratory check the data carry on analysis.result:pcv and small labium seamy side the most familiar(91.3%) skin external appearance with floss form familiar(62.3%) be located on a roe of fish form a time it;(33.33%)organization pathology show the upper part in the ji layer to fill the air a sex net basket a form empty bubble cell kind change;the acetic acid experiment a rate;(97.17%)human milk head lump virus second type examination feminine gender.conclusion:pcvhave a clinical characteristics of show the zhao, acetic acid of experiment hpv examination have importance value towards discriminate analysis.

目的：探讨女阴假性湿疣的临床病理特点及鉴别判断。方法：对69例患者的临床及实验室检查资料进行分析。结果：女阴假性湿疣及小阴唇内侧最为常见(91.3％)皮肤外观以绒毛状常见(62.3％)位于鱼子状次之(33.33％)；组织病理示棘层中上部弥漫性网篮状空泡细胞样改变；醋酸的试验率(97.17％)；人乳头瘤病毒亚型检测阴性。结论：女阴假性湿疣具有显著的临床特点，醋酸的试验hpv检测对鉴别分析有重要价值。

Students will learn Regression Analysis, Multivariate Analysis of Variance, Discriminate Analysis, Categorical Data Analysis, Principal Component Analysis, Canonical Correlation Analysis, Factor Analysis, Cluster Analysis, and Multidimensional Scaling Analysis.

同学们将在本课程中学习回归分析、多变量共变数分析、鉴别分析、类别资料分析、主成分分析、正典相关分析、因素分析、集群分析、多元尺度分析常用的多变量分析模式。

Besides, by using above-mentioned methods to attest the accuracy of factors, the correct percentage of each model are closely, that are 78.19% of logistic regression analysis, 78.06% of discriminate analysis and 78.45% of probit regression analysis.

另本研究所建构之覆核模型，其总正确率分别为：Logistic回归分析为78.19%，鉴别分析为78.06%，Probit回归分析为78.45%，三者之间差异极小，但以Probit回归分析所获之预测能力较佳。

Firstly, DWT is applied to the image, and moment invariants is extracted on fixed-size blocks of low-frequency component in wavelet sub-band to yield a reduced dimension representation.

然而，许多实际情况是要求在不依赖任何预签名提取或预嵌入信息的前提下，对图像的真伪和来源进行鉴别，这就是图像盲取证技术，也叫被动取证技术，它是一种新的图像鉴别分析思路。

In this paper, a novel two-dimensional kernel maximum scatter difference discriminant analysis (2D-KMSDA) is developed for the extraction of nolinear feature by using the well-known "kernel trick". It extracts much more effective nolinear feature and made the true recognition rate raise saliently. What's more, it also offers a unified framework for two-dimensional nolinear discriminant analysis.

本文通过引入著名的&核技巧&，将二维最大散度差线性鉴别分析扩展到非线性空间，提出了一种新的二维核最大散度差鉴别分析方法，该方法不仅抽取了图像中更加有效的非线性鉴别特征，使正确识别率显著提高，而且为二维非线性鉴别分析提供了一个统一的构架。

Linear projection analysis, including principal component analysis (or K-L transform) and Fisher linear discriminant analysis, is the classical and popular technique for feature extraction.

线性投影分析，包括主分量分析和Fisher线性鉴别分析，是特征抽取中最为经典和广泛使用的方法。

Linear projection analysis, including principal component analysis (or K-L transform) and Fisher linear discriminant analysis, is the classical and popular technique for feature extraction.

线性投影分析，包括主分量分析和Fisher线性鉴别分析，是特征抽取中最为经典和广泛使用的办法。

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。

与鉴别分析相关的网络解释 [注：此内容来源于网络，仅供参考]

CID CallingSubscriberIdentification：呼叫用户的鉴别

CPA CallingProcessorAnalysis 调用程序分析 | CID CallingSubscriberIdentification 呼叫用户的鉴别 | CPE CallonParityEven 调用奇偶位偶数(指令)

correlation analysis：相关分析法

(一)项目分析:本研究问卷题项进行项目分析,采用决断值(Critical Ratio, CR)与相关分析法(Correlation Analysis)作为选择题目之参考. 当决断值达显著水准(α值为0.05)时,表示该题能鉴别不同受试者的反应程度,因此可以选择,反之则应以删除,

Discriminant analysis：鉴别分析

较早使用多变量预测的是美国纽约大学的教授爱德华 阿尔曼(Edwardi.altman),他是第一个使用鉴别分析(discriminant analysis)研究企业失败预警的人. 他选取了1946~1965年间的33家破产的和正常经营的公司,使用了22个财务比率来分析公司潜在的失败危机.

FDA：abbr. fisher discriminant analysis; fisher鉴别分析

chemical kinetics：化学反应动力学

化学发光免疫分析法|chemiluminescence immunoassay, CIA | 化学反应动力学|chemical kinetics | 化学鉴别|chemical identification

Lynx lynx：猞猁

我们采集到了36个排泄物样品,但具体物种鉴别还有待于DNA分析作出结论. 在高山区,经常发现狼獾(Gulo gulo)和猞猁(Lynx lynx)的踪迹. 有蹄类方面,分布最广泛的物种有马鹿(Cervus elaphus)、麝、驼鹿(Alces alces)和野猪(Sus scrofa).

differential systematics：差别分类学,分析分类学

differentialstaining 鉴别染色法 | differential systematics 差别分类学,分析分类学 | differentiated 区别,分化

Alces alces：驼鹿

我们采集到了36个排泄物样品,但具体物种鉴别还有待于DNA分析作出结论. 在高山区,经常发现狼獾(Gulo gulo)和猞猁(Lynx lynx)的踪迹. 有蹄类方面,分布最广泛的物种有马鹿(Cervus elaphus)、麝、驼鹿(Alces alces)和野猪(Sus scrofa).

Xanthomonas axonopodis：地毯草黄单胞菌

引起一品红细菌性叶斑病的3个细菌菌株的碳源利用能力(Biolog)图谱仅能将它们归类到黄单胞属,而难以在种的水平上加以鉴别;虽然它们的脂肪酸分析(FAME)图谱都显示了和地毯草黄单胞菌(Xanthomonas axonopodis)最大的相似度,但相似值仍难以确定种.

Complaints：投诉

要求器械在一套质量体系下进行设计以满足这些规程;要求器械在该质量体系下制造;要求产品符合这些规程;要求器械能正确地安装、检查和维修;要求分析质量数据以鉴别和纠正质量问题;并要求投诉(complaints)能被处理.