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模式识别PCA(principle component analysis)源码.matlab 格式。PCA为经典而且经常使用的算法。-pattern recognition PCA (principle component analysis) source. Matlab format. PCA to the classic and often use the algorithm.
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Principle Component Analysis matlab源码
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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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它是SourceForge上的一个开源项目,使用Malib实现实时处理,CSU Face Identification Evaluation System进行人脸识别。算法包括:主成份分析(principle components analysis (PCA)),a.k.a eigenfaces算法,混合主成份分析,线性判别分析(PCA+LDA),图像差分分类器(IIDC),弹性图像匹配算法(EBGM)等等
Malic is realtime face recognition system
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This is a MFC program to test Principle Component Analysis (PCA) for constructing Eigenfaces. Using train images, it calculates Eigen values and Eigen vectors with sorting. Then reconstruct test images from PCA coefficients.
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document about principle component analysis
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document about principle component analysis
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document about principle component analysis
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document about principle component analysis
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document about principle component analysis
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document about principle component analysis
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共享主成份尺度不变变换PCA-SIFT代码,用于SAR图像配准,希望对各位雷达爱好者和SAR工作者有用!-Principle component analysis, PCA- Scale invariant feature transform-SIFT used for SAR processing.
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关于独立成分分析的一个ppt,这个ppt对独立成分分析的介绍很全面,从原理,到算法实现都很清楚,希望对大家有所帮助!-With regard to independent component analysis, a ppt, the ppt presentation on independent component analysis is very comprehensive, from the principle, to the algorithm are well aware, we wan
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神经计算的实验作业。用principle components analysis计算模式的主分量。提取线性输入的特征。-Neural computing experiment operations. Computing model using principle components analysis of the principal component
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principle component analysis example
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principle component analysis programme
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Principle component Analysis based face recognition system
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principle component analysis
using matlab
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利用Matlab编程实现主成分分析,
Cwstd.m——用总和标准化法标准化矩阵
Cwfac.m——计算相关系数矩阵;计算特征值和特征向量;对主成分进行排序;计算各特征值贡献率;挑选主成分(累计贡献率大于85 ),输出主成分个数;计算主成分载荷
Cwscore.m——计算各主成分得分、综合得分并排序
Cwprint.m——读入数据文件;调用以上三个函数并输出结果
-The use of principal component analysis Matlab programmi
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Independent component analysis and Principle component analysis PCA
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