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Description: 主成分分析在SPSS中的操作应用，可以对数据进行综合评价。很详细-Principal component analysis in SPSS in the operation of the application, you can conduct a comprehensive evaluation of data. Detail
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Size: 538624 |
Author: caiweihua |
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Description: 主成分分析，人脸识别，模式识别，对图像处理有点帮助-Principal component analysis, face recognition, pattern recognition, image processing for a little help
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Size: 2048 |
Author: ydq |
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Description: 基于核函数的主分量分析法源代码，可用于人脸识别-Kernel-based principal component analysis source code, can be used for face recognition
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Size: 27648 |
Author: xiechaocheng |
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Description: Probabilistic Principal Component Analysis
– Latent variable models
– Probabilistic PCA
• Formulation of PCA model
• Maximum likelihood estimation
– Closed form solution
– EM algorithm
» EM Algorithms for regular PCA
» Sensible PCA (E-M algorithm for probabilistic PCA)
– Mixtures of Probabilistic Principal Component
Analysers-Probabilistic Principal Component Analysis
– Latent variable models
– Probabilistic PCA
• Formulation of PCA model
• Maximum likelihood estimation
– Closed form solution
– EM algorithm
» EM Algorithms for regular PCA
» Sensible PCA (E-M algorithm for probabilistic PCA)
– Mixtures of Probabilistic Principal Component
Analysers
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Size: 263168 |
Author: Tatyana |
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Description: 核主成分分析中使用多项式核函数时的MATLAB代码，有注释，易看懂。-Kernel Principal Component Analysis in the use of polynomial kernel function of the MATLAB code, annotated, easy read.
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Size: 1024 |
Author: shane |
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Description: 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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Size: 1024 |
Author: 萧茅律 |
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Description: 用Matlab实现主成分分析（PCA)算法.-Principal component analysis using Matlab implementation (PCA) algorithm.
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Size: 114688 |
Author: zifei |
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Description: pdf for fingerprint from ieee include:
PIPELINED MINUTIAE EXTRACTION FROM FINGERPRINT IMAGES
A Novel Principal Component Analysis Neural Network Algorithm for Fingerprint Recognition
in Online Examination System
Processing of Distorted Fingerprints with use of Three-Rate
Hybrid Kohonen Neural Networks
nad etc
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Size: 21190656 |
Author: ali |
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Description: 一个关于主成分分析的matlab演示，十分有用-A principal component analysis on matlab demo, very useful
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Size: 1024 |
Author: Chen Fang |
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Description: 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 for data transformation and dimensionality reduction. Kernel ECA reveals structure relating to the Renyi entropy of the input space data set, estimated via a kernel matrix using Parzen windowing. This is achieved by projections onto a subset of entropy preserving kernel principal component analysis (kernel PCA) axes. This subset does not need, in general, to correspond to the top eigenvalues of the kernel matrix, in contrast to the dimensionality reduction using kernel PCA. We show that kernel ECA may produce strikingly different transformed data sets compared to kernel PCA, with a distinct angle-based structure. A new spectral clustering algorithm utilizing this structure is developed with positive results. Furthermore, kernel ECA is shown to be an useful alternative for pattern denoising.
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Size: 3072 |
Author: johhnny |
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Description: 利用主成分分析方法，对TE模型产生的故障数据故障1进行故障检测-Using principal component analysis, on the TE model failure data generated by a fault detection fault
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Size: 1024 |
Author: viola |
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Description: matlab关于主成分分析的代码，使用于经济医疗等分析-a program code on matlab of principal component,it s used in economic,healthy and so on.
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Size: 3072 |
Author: 吕介民 |
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Description: [K,H,P1,P2] = surfature(X,Y,Z) returns the gaussian curvature of a surface (K), mean curvature (H), and principal curvatures (P1,P2). The inputs (X,Y,Z) are 2D arrays corresponding to the surface being analyzed.
Example
[X,Y,Z] = peaks
[K,H,P1,P2] = surfature(X,Y,Z)
surf(X,Y,Z,H, facecolor , interp )
set(gca, clim ,[-1,1])
-[K,H,P1,P2] = surfature(X,Y,Z) returns the gaussian curvature of a surface (K), mean curvature (H), and principal curvatures (P1,P2). The inputs (X,Y,Z) are 2D arrays corresponding to the surface being analyzed.
Example
[X,Y,Z] = peaks
[K,H,P1,P2] = surfature(X,Y,Z)
surf(X,Y,Z,H, facecolor , interp )
set(gca, clim ,[-1,1])
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Size: 1024 |
Author: tao lu |
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Description: Camera calibration consists in the estimation of a model for an un-calibrated camera. The objective is to find the external parameters (position and orientation relatively to a world co-ordinate system), and the internal parameters of the camera (principal point or image centre, focal length and distortion coefficients). One of the most used camera calibration techniques is the one proposed by Tsai
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Size: 1192960 |
Author: Ahmed |
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Description: MPCA Multilinear Principal Component Analysis of Tensor Objects with MATLAB
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Size: 2073600 |
Author: javad |
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Description: The Principal component analysis, is a standard technique used for data reduction in statistical pattern recognition and signal processing
A common problem in statistical pattern recognition is feature selection or feature extraction. Feature selection is a process whereby a data space is transformed into a feature space that theory has exactly same dimension as the original data space. However the transformation is designed in such a way that the data set is represented by a reduced number of “effective features” and most of the intrinsic information content of the data or the data set undergoes a dimensionality reduction.
PCA
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Size: 13312 |
Author: binu |
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Description: 主成分分析法步骤，例子,详细讲解及方法-Principal Component Analysis
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Size: 218112 |
Author: liangguoxiong |
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Description: 列主元高斯消去法，数值计算必备方法，通俗易懂-principal component gaussian elimination
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Size: 361472 |
Author: 刘翔东 |
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Description: 列主元消去法在VC++环境中运行用于计算方法作业-Principal component elimination method in the column VC++ environment to run operations for the calculation of
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Size: 753664 |
Author: 冯裴裴 |
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Description: 用于主成分分析（PCA）,包括，原变量相关系数矩阵的特征向量和特征值的求解，主成分的提取，载荷值的确定等-Used principal component analysis (PCA), including the original variable correlation matrix eigenvectors and eigenvalues of the solution, the main component of the extract, load values to determine the other
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Size: 2048 |
Author: 追风 |
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