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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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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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独立分量分析的原理与应用，大家看看，一个很有用-Principle and Application of independent component analysis, we look at a useful
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principle component analysis
using matlab
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principle component analysis is one of most powerful method for feather extraction
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kernel principle component analysis 故障检测-kernel principle component analysis fault detection
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This the code for PCA (Principle component analysis). First PCA is used for dimension reduction. And then KNN is applied for classification.-This is the code for PCA (Principle component analysis). First PCA is used for dimension reduction. And then
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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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this about principle component analysis is used for dimension reduction -this is about principle component analysis is used for dimension reduction
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一个师兄的毕设，利用贝叶斯原理估计混合logit模型的参数，独立成分分析算法降低原始数据噪声。- A complete set of brothers, Bayesian parameter estimation principle mixed logit model, Independent component analysis algorithm reduces the raw data noise.
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包括邓氏关联度、绝对关联度、斜率关联度、改进绝对关联度,基于负熵最大的独立分量分析，利用贝叶斯原理估计混合logit模型的参数。- Including Deng s correlation, absolute correlation, correlation of slope, improved absolute correlation, Based on negative entropy largest independent component analysis, Bayesian para
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实现了图像的加水印，去噪，加噪声等功能，IMC-PID是利用内模控制原理来对PID参数进行计算，独立成分分析算法降低原始数据噪声。- Realize image watermarking, de-noising, plus noise and other functions, The IMC- PID is using the internal model control principle for PID parameters is calculated, Independent compon
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PCA（principle component analysis）算法，可用于特征选择等，希望有帮助(principle component analysis)
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Independent component analysis and Principle component analysis PCA
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