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主分量分析实现人脸识别人脸识别matlab源代码，应用主分量分析（PCA）实现了人脸识别。-Principal component analysis of face recognition
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PCA 主成分分析 特征抽取 特征降维 matlab实现-PCA principal component analysis feature extraction dimension reduction
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支持向量机（SVM）主成分分析法进行预处理筛选变量- support vector machine (SVM)，PCA(principal component analysis)
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PCA 主成分分析 程序 采用主成分分析法（PCA），对大沽夹河流域水质进行了定量化综合评价。
-matlab PCA(Principal Component Analysis) programmer is deserved ,it s good to learn.The water quality in Dagujia River basin was assessed by using the PCA method
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基于主成分分析法和反向传输神经网络的语音情感识别
摘要——语音信号中包含着丰富的情感信息，尤其是语义信息。快乐、愤怒、厌恶、恐惧、悲伤，这五种基本情感是经过一个受认可的框架讨论和公认的，这个框架包括主成分分析法和BP神经网络。通过PCA从43种候选参数中筛选出11种参数作为确定某种特定的情感类别的标准。实验采用两种神经网络模型，One Class One Network 和 All Class One Network，并进行比较。实验结果表明，其可靠性达52 ~62 ，这说明用这种框架来识别
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PCA(主成分分析)的MATLAB源代码，包含测试例子及使用文档，该算法主要用于图像分类时特征的降维。-PCA (Principal Component Analysis) of the MATLAB source code, including test case and use the document, the algorithm is mainly used for image classification and feature dimensionality reduction.
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基于pca主成分分析实现人脸识别功能，是人脸识别中比较较经典的算法之一，取得很好的效果，已通过测试。
-Pca-based principal component analysis of face recognition feature is face recognition than the classic algorithm achieved very good results, has been tested.
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PCA(主成分分析法)、LDA(线性判别法)两种方法是主要的的线性降维法，有非常好的效果，希望对大家能够有用！ 已通过测试。
-PCA (Principal Component Analysis), LDA (linear discriminant method) two methods are the main linear dimensionality reduction method, with very good results, we hope to be useful! Has
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pca与ica相结合的特征选择,进行主成分分析以后，再对所得特征进行独立成分分析-the combination of pca and ica for feature selection，after Principal component analysis, the resulting characteristics is has a independent component analysis
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用Matlab实现PCA主成分分析函数、例程-PCA principal component analysis with Matlab routine functions
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2D双向PCA(2D2PCA),二维主成分分析(2DPCA)的实质是对图像矩阵按行进行图像压缩抽取特征,消除了图像列的相关性.-2D bidirectional PCA (2D2PCA), two-dimensional principal component analysis (2DPCA) real image matrix row the Image Compression extraction characteristics to eliminate the correlation of
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pca主成分分析，改进的pca程序源代码-pca principal component analysis, improved pca program source code
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pca principal component analysis
with medical image-principal component analysis
with medical image
can make the dimension of the image as short as possible which is easy for us to compare their similiarities
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基于PCA主成分分析算法的人脸识别，包括Matlab代码及原理的PPT
-Face recognition algorithm based on PCA principal component analysis, including Matlab code and the principle of the PPT
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这是外国人实现的非线性主成份分析，可下载相应的文章，可用来降维！-Applies the kernel method to unsupervised algorithms as for instance Principal Component Analysis. This gives a principled and efficient approach to nonlinear PCA
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用PCA主成分分析進行錯誤訊號分離
可應用在晶圓製程資料的分析-PCA principal component analysis of the error signal separation can be applied to the wafer process data analysis
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利用主成分分析方法pca对数据进行降维处理和故障检测-Pca using principal component analysis for data dimensionality reduction and fault detection
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简单的人脸识别matlab小程序，基于PCA算法，可自己添加主成分分析-Simple face recognition matlab small procedures, based on PCA algorithm can add their own principal component analysis
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. PCA人脸识别
A．闭集测试。用每个人的前5张图像作为训练，剩下的5张图像作为测试。也就是说总共有200张训练图像和200张测试图像。采用最近邻分类，分析选取不同的主分量个数K，对识别率的影响
-. PCA Face Recognition A. Closed set tests. With each of the first five images for training, the remaining 5 images as a test. That is a total of
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Function to perform Principle Component Analysis over a set of training
vectors passed as a concatenated matrix.
Usage:- [V,D,M] = pca(X,n)
[V,D] = pca(X,aM,n)
where:-
<input>
X = concatenated set of column vectors
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