搜索资源列表
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一个很好的PCA程序。它可用于数据的降维,消噪及特征提取。,A good PCA procedures. It can be used for data dimensionality reduction, de-noising and feature extraction.
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普通降维方法汇总,PCA,LDA,isomap-Summary of general dimension reduction methods, PCA, LDA, isomap .......
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dctcom.m文件利用DCT变换完成对输入图像进行压缩;imagecbe.m完成对输入的两幅RGB图像用小波分析的方法进行图像融合 imagecom.m完成对输入的RGB图像用小波分析的方法进行自动降噪,得到高频系数阈值,降噪效果百分比和结果 wavelet1D.m完成对输入的一维信号进行多尺度离散小波分解 wavelet2D完成对输入的二维信号进行多尺度离散小波分解;zigzag.m完成对输入的8*8矩阵按照zigzag排列抽取数据.-document the use of DCT tran
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pca算法的matlab实现 主成分分量分析可用于数据的降维和模式识别问题 -pca algorithm matlab component analysis to achieve the principal component can be used for data dimensionality reduction and pattern recognition problem
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lda 源码。用来为数据降维,使得识别率有所提高。-lda source code. Is used for data dimensionality reduction, making the recognition rate increased.
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用于特征降维,特征融合,相关分析等多元数据分析的典型相关分析Matlab代码实现。-For feature reduction, feature fusion, correlation analysis, multivariate data analysis, canonical correlation analysis of Matlab code implementation.
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用于特征降维,特征融合,相关分析等多元数据分析的鉴别型典型相关分析(DCCA)Matlab代码实现。-For feature reduction, feature fusion, multivariate data analysis and correlation analysis based identification of canonical correlation analysis (DCCA) Matlab code implementation.
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用于特征降维,特征融合,相关分析等多元数据分析的广义典型相关分析(GCCA)Matlab代码实现。-For feature reduction, feature fusion, correlation analysis, multivariate data analysis using generalized canonical correlation analysis (GCCA) Matlab code implementation.
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用于特征降维,特征融合,相关分析等多元数据分析的fisher鉴别分析(FLDA)Matlab代码实现。-For feature reduction, feature fusion, correlation analysis, multivariate data analysis of the fisher discriminant analysis (FLDA) Matlab code implementation.
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用于特征降维人脸识别等多元数据分析的主分量分析投影的Matlab代码实现。-For feature reduction and other multivariate data analysis, face recognition principal component analysis projection of the Matlab code implementation.
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Kernel Entropy Component Analysis,KECA方法的作者R. Jenssen自己写的MATLAB代码,文章发表在2010年5月的IEEE TPAMI上面-Kernel Entropy Component Analysis, by R. Jenssen, published in IEEE TPAMI 2010.
We introduce kernel entropy component analysis (kernel ECA) as a new method
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主元分析,主要用于多维数据的降维处理,能够从多维数据中提取出最主要的元素,从线性变换的角度来说就是坐标表换到一个能够体现系统特征的基座标系上-Principal component analysis, multidimensional data is mainly used for dimension reduction process, multi-dimensional data can be extracted from the most important elements, from
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pca算法的matlab实现,进行数据的降维处理-Pca algorithm matlab, the data dimension reduction processing
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最新最强MATLAB降维工具箱,可用于人脸识别,模式识别,机器学习,数据挖掘,图像处理等领域,里面包含的算法有PCA,LDA,KPCA,KLDA,Laplacian,LPP,MDS,NPE,SPE,LLC,CFA,MCML,LM-The latest and greatest dimension reduction MATLAB toolbox can be used for face recognition, pattern recognition, machine learning, dat
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使用yale人脸数据库,用PCA降维方法来对人脸数据进行分类的MATLAB代码,附有人脸图片-Yale face , using PCA dimension reduction method to classify data of face of MATLAB code, and comes with a human face images
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三维点云包围盒精简算法,内包含点云数据与处理结果,直观可用,效果良好。(Three dimensional point cloud bounding box reduction algorithm, which contains point cloud data and processing results, is intuitive and available, and the effect is good.)
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高光谱图像在matlab上处理数据波段,并且包括降维功能(Hyperspectral images deal with data bands on MATLAB and include dimensionality reduction functions)
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