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rtejfgds
- 现有的代数特征的抽取方法绝大多数采用一维的方法，即首先将图像转换为一维向量，再用主分量分析（PCA）,Fisher线性鉴别分析（LDA）,Fisherfaces式核主分量分析（KPCA）等方法抽取特征，然后用适合的分类器分类。针对一维方法维数过高，计算量大，协方差矩阵常常是奇异矩阵等不足，提出了二维的图像特征抽取方法，计算量小，协方差矩阵一般是可逆的，且识别率较高。-existing algebra feature extraction method using a majority of th
p-c-a
- 用于图像识别和特征提取时的主成分分析程序，采用Matlab编写。-for image recognition and feature extraction of principal component analysis procedures, the preparation of Matlab.
Pca-extraction
- pca进行特征提取源码，用matlab语言编写，pca即主成分分析-pca source for feature extraction using Matlab language, pca that Principal Component Analysis
pca
- 这是一个模式识别中关于主成分分析的特征提取的matlab源码-This is a pattern recognition on the Principal Component Analysis Feature Extraction of Matlab FOSS
stprtool.rar
- 统计模式识别工具箱（Statistical Pattern Recognition Toolbox）包含： 1，Analysis of linear discriminant function 2，Feature extraction: Linear Discriminant Analysis 3，Probability distribution estimation and clustering 4，Support Vector and other Kernel Machines,
PCA.rar
- 用主成分分析法提取人脸图像特征的程序，算法理论依据是K-L变换,Principal Component Analysis with face image feature extraction process
MPCACodes.rar
- 编程主要用于脸部特征提取，而且是三维图像。,Multilinear principal component analysis algorithm for face feature extraction.
PCA
- PCA,主成分分析，可应用于矩阵降维，人脸特征提取及人脸识别。-PCA, principal component analysis, can be applied to matrix reduction, facial feature extraction and face recognition.
PCA
- 用来进行主成分分析，实现数据压缩功能，也可以做特征提取与分类-Be used for principal component analysis, data compression, you can also do feature extraction and classification
pca
- PCA主成分分析，用于人脸识别，特征提取等-PCA principal component analysis for face recognition, feature extraction, etc.
Subpattern-based_principal___component_analysis.zi
- 子模式主成分分析首先对原始图像分块，然后对相同位置的子图像分别建立子图像集，在每一个子图像集内使用PCA方法提取特征，建立子空间。对待识别图像，经相同分块后，分别将子图像向对应的子空间投影，提取特征。最后根据最近邻原则进行分类。-Sub-mode principal component analysis first of the original image block, and then the same sub-image, respectively, the location of the
featureExtraction
- 该程序包实现了模式识别中的两个特征提取算法，主成分分析PCA和线性判别分析LDA。采用C++语言编写，开发环境VS。 程序包还提供了两个测试样本文件。-The package to achieve the recognition of the two feature extraction algorithm, principal component analysis PCA and linear discriminant analysis LDA. Using C++ language, dev
MPCALDA
- 编程是由pca和lda结合的脸部特征提取，用于三维图像。-multilinear principal component analysis combined with Linear discriminant analysis 3D face feature extraction.
KPCA
- 核主成分分析方法，是主成分分析的一种改进算法，是一种非线性的特征提取方法。 -Kernel principal component analysis, is the principal component analysis of an improved algorithm, is a nonlinear feature extraction method.
progarmlab4
- The Principal component analysis, is a standard technique used for data reduction in statistical pattern recognition and signal processing A common problem in statistical pattern recognition is feature selection or feature extraction. Feature selec
face-recognition
- pca又称主成分分析，主要用来提取图像的主要成分，作为特征提取一个重要算法，将其用于人脸识别-pca, also known as principal component analysis, mainly used to extract the main component of the image, as a key feature extraction algorithm, be used in face recognition
tezhentiqu
- 论文使用一种经典的特征提取方法—主成分分析法（PCA）进行特征提取，其基本思想是降维。降维后的数据除了计算工作量减少之外不会减少原始数据所包含的有效信息量。-This paper use a classical method for feature extraction—Principal Component Analysis(PCA)with the basic idea of dimensionality reduction(it still contains all valid infor
Feature
- 关于特征提取的文章和代码，基于稀疏化的主成分分析法的，还没运行过，应该不错，共享-Articles and code feature extraction method based on principal component analysis sparse, not run, it should be good, sharing
principal-component-analysis
- 主成份分析在模式识别中是一种特征提取方法！-a very important technique feature extraction in pattern recognazition
Feature_extraction
- 用于运动人体的图像特征提取，提取的特征包括，高宽比，速度，紧密度，灰度共生矩阵，hu矩，主成分分析，离散余弦变化，图像的预处理等。(Image feature extraction for moving human body includes features such as aspect ratio, speed, tightness, gray level co-occurrence matrix, Hu moments, principal component analysis, disc