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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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编程主要用于脸部特征提取，而且是三维图像。,Multilinear principal component analysis algorithm for face feature extraction.
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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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编程是由pca和lda结合的脸部特征提取，用于三维图像。-multilinear principal component analysis combined with Linear discriminant analysis 3D face feature extraction.
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基于PSO训练SVM的人脸识别利用支持向量机在学习能力方面表现的良好性能,结合核主元分析特征提取方法,将将其应用于人脸识别中,该方法在实验中表现了良好的识别性能,为人脸识别领域提供了一条新的识别途径 已通过测试。
-Good performance, performance in the ability to learn the use of support vector machines based on PSO training SVM face recognition combined
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人脸识别论文
An Efficient Method for Face Feature Extraction and
Recognition based on Contourlet Transform and Principal
Component Analysis using Neural Network -An Efficient Method for Face Feature Extraction and
Recognition based on Contourlet T
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核主成分分析是一种流行的非线性特征提取方法-
Kernel principal component analysis is a popular nonlinear feature extraction method
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自己编写的主成分分析法的代码，可用于定位中特征的提取-Write your own code of principal component analysis (pca), can be used to locate in feature extraction
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是学习PCA特征提取的很好的学习资料，ICA（主分量分析）算法和程序，计算目标和海洋回波的功率谱密度。- Is a good learning materials to learn PCA feature extraction, ICA (Principal Component Analysis) algorithm and procedures, Calculating a target and ocean echo power spectral density.
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特征降维；特征抽取；PCA；主成分分析法；C-Feature reduction feature extraction PCA principal component analysis C++
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是学习PCA特征提取的很好的学习资料，D-S证据理论数据融合，多元数据分析的主分量分析投影。- Is a good learning materials to learn PCA feature extraction, D-S evidence theory data fusion, Principal component analysis of multivariate data analysis projection.
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用于信号特征提取、信号消噪，借鉴了主成分分析算法（PCA），LCMV优化设计阵列处理信号。- For feature extraction, signal de-noising, It draws on principal component analysis algorithm (PCA), LCMV optimization design array signal processing.
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用于图像识别和特征提取时的主成分分析程序,采用Matlab编写,(When used in image recognition and feature extraction of principal component analysis procedure, using Matlab,)
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Contains the eigenvalue and eigenvector extraction, the training sample, and the final recognition, Principal component analysis of multivariate data analysis projection, For feature extraction, signal de-noising.
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