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主成分分析（pcA）人脸识别，在ORL库上进行测试，产生矩阵为散步矩阵-Principal component analysis (pcA) recognition, tested on the ORL database, resulting in a walk matrix matrix
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该代码为PCA主成分分析，可用于特征选择，选取贡献最大的前三个主成分-The code for the PCA principal component analysis, can be used for feature selection, select the largest contribution to the first three principal components
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PCA主成分分析算法用于人脸识别的例子。此算法是基于矩阵特征值的排序而提取出主要成分的。-PCA principal component analysis algorithm for face recognition example. This algorithm is based on the ranking of the matrix eigenvalue extracted principal components.
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利用主分量分析(PCA)进行模式识别，包括主分量分析运算的主要函数，以及相关应用的例子。-Using principal component analysis (PCA) for pattern recognition, including the principal component analysis of the main function of computing, and related application examples.
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PCA:Principal Components Analysis
It computes Principal Component Analysis, i.e., the linear transform which makes data uncorrelated and minize the reconstruction error.
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本程序基于MATLAB仿真工具实现主分量分析-The program is based on MATLAB simulation tools principal component analysis
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Principal Component Analysis
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用matlab 7.0 编的 主成分分析程序（GUI）-principal component analysis program （matlab7.0 GUI）
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用于主成分分析(pca）的程序（c++）-principal component analysis C++ program
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Principal component analysis (PCA) is a mathematical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of uncorrelated variables called principal components. The nu
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c语言实现主成份分析的程序pca，对做主成分分析的朋友很有价值-c language program principal component analysis pca, Friends of the shots valuable component analysis
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主成分分析，及其用于人脸识别的算法实现。-Principal component analysis, and for the face recognition algorithm.
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pca主成分分析算法matlab源码，利用matlab实现pca算法。附带pca相关资料-pca principal component analysis algorithm matlab source code, the use of matlab to achieve pca algorithm. Pca with information ... ...
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光谱空间的主成分分析 PCA ：旨在利用降维的思想，把多指标转化为少数几个综合标。-Principal component analysis of spectral space PCA: dimension reduction ideas to use to index into a few more comprehensive standard.
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本文阐述了基于主元分析的拉普拉斯金字塔图像融合的原理和方法:首先对原图像分别进行拉普拉斯
金字塔分解,然后分别对高频部分采用主元分析（PCA）法融合,对低频部分采用平均梯度法进行融合,最后对
拉普拉斯金字塔做反变换得到最终的融合图像。通过对可见光与红外图像的融合，以及对不同焦距图像融合
的结果分析，该算法比单纯的PCA和拉普拉斯图像融合能得到具有更多有用信息的高对比度的融合图像-In this paper, principal component analysis based on
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一个最简单的主成分分析的源代码，希望对朋友们有所价值-A simple principal component analysis of the source code, I hope my friends have value
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实现了模式识别中主成分分析（PCA）算法，可以对目标快速分类-To achieve the pattern recognition principal component analysis (PCA) algorithm, can be quickly classified on the target
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这篇文章是盲信号处理，因为是英文文章，所以大家看内容就好了。-Principal component analysis (PCA) is a mainstay of modern data analysis- a black box that
is widely used but poorly understood. The goal of this paper is to dispel the magic behind this
black box. This tutorial foc
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Principal component analysis (PCA) is a mathematical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of uncorrelated variables called principal components.
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使用principal component analysis PCA减少特征数目-Use principal component analysis (PCA) to reduce the number features.
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