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empca2.tar
- 模式分类中应用到的PCA算法，包括其奇异值分解SVD算法。可用来降维提取主元素等。-pattern classification applied to the PCA algorithm, including its SVD singular value decomposition algorithm. Can be used to take down the main Viti Levu and other elements.
pcakenelfunction
- pca分解的核函数，在pca分解中可以用到，特别是分解的矩阵维数比较高的情况下，通过svd分解获得pca基-pca decomposition of the kernel function, in the pca decomposition can be used, in particular the decomposition of the matrix of higher dimension, through the svd decomposition was pca-based
PCA_for_3_component_compound
- 该程序旨在模拟处理分析多种化学物质混合物的吸收光谱数据，提取出各个化学成分的峰值所在。该程序采用svd方法对光谱数据的协方差矩阵进行PCA分析，并且取得令人满意的效果。-The program designed to simulate the processing and analysis of multiple chemical mixtures of the absorption spectra of the data, extracting the chemical composition
Eigenfaces
- Eigenfaces tests for grayscale images using PCA and SVD
matlab
- ) 使用分块的主成分分析方法(PCA)对人脸图像进行压缩编码。针对PCA方法计算量大的缺点,首先把问题转化成奇异值分解(SVD)问题,然后设计了特征空间的更新算法,通过递推,简化每一步计算的计算量,达到了实时编码的要求。 4) 在Windows平台下基于Video for Windows(VFW)接口开发了人脸视频图像编码和解码的实验系统,该系统实现了图像采集、图像显示、编码、解码等功能。-) The use of sub-blocks of principal component analys
ComputeEigenfaces
- svd提取特征脸，Computer Vision课程作业，用PCA计算特征脸，提取主成分，用PCA系数进行相似度计算。-comupute face similarity using eigenface and PCA analysis
CSE_Assignment3
- I am submitting my Computational science and engineering assignment #3 based on SVD/PCA.The zip file contains matlab codes of Exercise no:1 and Exercise no:3 as program_1.m and program_3.m files respectively. I have made a separate reports for
Face-Recognition
- Face Recognition By PCA using SVD technique .
reduce-dimention-of-face-recognition
- 在人脸识别中的降维问题，应用PCA和SVD等方法来分析和解决-Dimensionality reduction in face recognition problems, the application of methods such as PCA and SVD to analyze and solve
KL_SVD_face_recognition
- PCA主成分分析，采用KL投影和SVD分解提取人脸特征向量，最后采用最近邻判别法计算识别率。-Face recognition based on PCA. KL projection and SVD are used to extract face eigenvectors. Recognition rate is calculated by k nearest neighbors(KNN) method.
SVD_eignface
- SVD进行特征脸提取，和PCA类似，选取前30个特征脸，并且将它显示这30个特征脸-SVD face feature extraction, and PCA is similar to the first 30 eigenfaces, and will it show that 30 eigenface
pythonsrc
- 机器学习算法，包括主成分分析方法，奇异值分解，逻辑回归，最小二乘法线性回归，朴素贝叶斯-machine learning algorithm prototype including PCA, SVD, Logic Regression, LMS and Naive Bayes
FaceRec
- 最新SVM和PCA的人脸识别系统,详细地给出了用SVM解决问题的一般框架-Latest SVD and PCA Face Recognition System
SVD-PCA-eig
- 本程序详细区别了matlab中pca、svd、eig三个函数的区别和联系。对于学习pca有极大帮助-This program detailing the differences between the differences and connections in matlab pca, svd, eig three functions. Pca great help for learning
pca using svd
- Principal components analysis is one of a family of techniques for taking high-dimensional data, and using the dependencies between the variables to represent it in a more tractable, lower-dimensional form, without losing too much information. PC
pcadenoise
- 矩阵 pca或者低秩方法去噪，利用svd分解，实现对图像矩阵的去噪，该方法支持对rgb图像的去噪。使用代码请 文章中表明出处，感谢。 感谢重庆市研究生科研创新项目支持，项目号CYS16183(image denoise by low-rand regularizer or pca method. the low rank is evaluted by svd, and this method is also support for rgb image.)
PCA
- 1、读入图片，根据PGN格式的line 2 确定矩阵的大小为 28*28=784，根据line4 获取. 2、读入图片，根据PGN格式的line 2 确定矩阵的大小为 28*28=784，根据line4 获取。 3、计算平均矩阵。 4、对平均值矩阵进行SVD： 5、平均矩阵进行SVD后的前20个singular vector的输出结果。 6. 将训练集的每一张图片当成一行，形成一个矩阵，然后对矩阵进行PCA分解。 7. 这个矩阵对测试集的每张图片进行降 维，得到的图像。(1, rea
PCA&SVD_Denoising
- 使用PCA和SVD进行数据去噪，利用数据主要的特征向量进行数据恢复和重建(Using PCA and SVD for data denoising)
降维code
- 了解降维、特征筛选等基本原理 掌握PCA、SVD、LAD和NMF等算法实现及应用(Understand the basic principles of dimensionality reduction and feature selection Master the algorithm implementation and application of PCA, SVD, lad and NMF)