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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
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结合PCA+LDA的图像识别算法VC封装类,PCA（主元素分析，光照敏感）,可用于人脸识别的初级算法-combination of image recognition algorithm VC Packaging category, PCA (principal component analysis, Light-sensitive), can be used for the initial face recognition algorithm
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应用PCA（主成分分析）进行人脸识别的matlab程序，有较高成功率-PCA (Principal Component Analysis) face recognition Matlab procedures, which have a higher success rate
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主成分分析算法（PCA），这是一个外国人编写的，很具有参考价值-principal component analysis algorithm (PCA), which was prepared by a foreigner, it is very valuable reference
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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
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PCA and PLS aims:to get some
insight into the bilinear factor models Principal Component Analysis
(PCA) and Partial Least Squares (PLS) regression, focusing on the
mathematics and numerical aspects rather than how s and why s of
data analysis
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pca人脸识别This package implements basic Principal Component Analysis in Matlab and
tests is with grayscale portion of the FERET database. Images are not
preprocessed and it is up to the user to preprocess the images as wanted,
not changing the fil
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利用Matlab编程实现主成分分析,从数学角度来看，这是一种降维处理技术-Using Matlab programming principal component analysis, from a mathematical point of view, this is a dimension reduction process technology
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C语言编写的PCA程序，实现主成分分析功能-C language of the PCA program to achieve the principal component analysis function
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降维工具箱，包含主元分析（PCA）,核主元分析（KPCA）等。-Dimensionality reduction kit, including principal component analysis (PCA), Kernel Principal Component Analysis (KPCA) and so on.
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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
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主要介绍主分量分析，怎样提取主要特征来重构原始信号。-Introduces the principal component analysis, extracting the main features of how to reconstruct the original signal.
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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
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详细介绍PCA（主成分分析），应用于人脸识别。PCA概念，发展，关键技术-Details on PCA (Principal Component Analysis), applied to face recognition. PCA concept, development, and key technologies
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图像融合算法，高通滤波法、IHS法、PCA主成分分析、小波融合、小波和IHS结合的融合方法-Image fusion algorithms, high-pass filtering, IHS method, PCA principal component analysis, wavelet fusion, wavelet and IHS fusion method combining
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人脸识别：使用PCA方法，即主成分分析，区分人脸和非人脸。主要用于随即过程大作业。-Face Recognition: Using the PCA method, that is, principal component analysis, the distinction between face and non-human face. Then the process used mainly for large operations.
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Principal Component Analysis源码，程序附带selfdemo演示-pca code
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pca主成分分析算法matlab源码,用于人脸识别中。-pca principal component analysis algorithm matlab source code for Face Recognition.
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principal component analysis in one dimension
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学习PCA即主成元分析不可不读的经典外文文献。有需要的朋友下~-PCA learning as the main element analysis that can not read the classic literature in foreign languages. In need of a friend of ~
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