搜索资源列表
feipca.rar
- 非线性PCA算法matlab程序段,完成独立分量分析的主分量分解,Non-linear PCA algorithm matlab program segment, the completion of independent component analysis of the principal component decomposition
rpca
- RobustPCA 是最近提出的一种非常新的图像矩阵分解算法,该算法具有对噪声不敏感、能处理高维图像数据的特点。这是论文作者提供的 MATLAB 实现代码。-Oct 2009 This matlab code implements the augmented Lagrange multiplier method for Robust PCA.
GaussPivot
- 利用高斯列主元消去法进行LU分解,并求解方程组-PCA out Gaussian elimination method and LU decomposition to solve equation
xuanzhuyuanduliteer
- 对任意阶线性方程组进行独立特尔选主元分解,并解出未知数-Of linear equations of arbitrary order to conduct an independent Ritter election PCA decomposition, and solution out of unknowns
exrealframetest
- 一个有关核PCA的程序 主要用于模式识别和正交分解中-A nuclear PCA process is mainly used for pattern recognition and orthogonal decomposition
Numerical-Analysis-5
- 这里面是数值分析作业的VB程序数值分析程序 线性方程 雅可比 高斯 迭代 二次及高次 线性微分方程 列主元及行主元高斯消元法 LU分解 插值法-This operation which is the numerical analysis numerical analysis program VB program Gaussian iterative linear Fangcheng Ya secondary and higher than linear differential column a
zuijinlinfenlei
- 我们使用MATLAB软件实现了人脸识别并统计其识别率。本实验采用PCA(主成分分析)方法,利用K-L变换和奇异值分解原理实现。并分别采用最近邻法分类器得出它们的成功率。-We use face recognition software and the MATLAB Statistics recognition rate. The present study, PCA (principal component analysis) method, using KL transform and sin
NMF1
- 非负矩阵分解和PCA有相同之处,但是具有更好的物理意义。-NMF and PCA have in common, but with better physical meaning.
PCAfusion
- 用PCA方法实现的图像融合程序,对图像进行了主成分分解-image fusion using the PCA method
CodesaImages
- 用于指纹检测等,利用图像的梯度方向,获得局部主导方向。Principal Component Analysis (PCA),包含有高斯金字塔分层,SVD奇异值分解,内含测试图像-Used for fingerprint detection, etc. Using the gradient direction of image to get local leading direction. Principal Component Analysis (PCA), contains a gaussi
117
- 针对非线性非平稳信号的去噪问题,提出一种基于主成分分析(PCA)的经验模态分解(EMD)消噪方法.该方法根据EMD的分解特性,利用PCA对噪声信号经EMD分解后的内蕴模态函数(IMF)进行去噪处理-For nonlinear and non-stationary signal de-noising is proposed based on principal component analysis (PCA) of the empirical mode decomposition (EMD) de
computing-method
- 列主元消去法解线性方程、三对角阵的LU分解、用迭代法解方程组、求矩阵的LDLT分解及cholesky分解、求函数插值多项式、插值误差、用复化公式求积分方程、计算定积分-Column pca elimination method solving linear equations, LU decomposition of tridiagonal matrix, solutions of equations by iteration method, LDLT decomposition of matr
matlab--jisuanfangfa
- 计算方法,实现LU分解,高斯列主元消去法,和多项式插值,样条插值等数值计算-Calculation methods to achieve LU decomposition, out PCA Gaussian elimination, and polynomial interpolation, spline interpolation numerical
123
- 用LU分解及列主元高斯消去法解线性方程组(非图形界面)。-Decomposition and out PCA Gaussian elimination method for solving linear equations with LU.
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.
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
PCA_K
- PCA的思想为将图像的协方差矩阵分解,获得分解后的方向向量。然后将数据分别投影到某一个方向上去,获得与原图象近似的图像。当然,与最大特征值所对应的特征向量方向获得最好的图像。因此,PCA方法可以作为降维的一种方法。留下在某些方向较好的图像,而抛弃那些在另外一些方向上不好的图像。-PCA ideas as to decompose the covariance matrix of the image, the direction vector obtained after decompositio
iexact_alm_rpca
- 鲁棒主成分分析 低秩与稀疏矩阵分解 增广拉格朗日 图像重建、去噪-robust pca low-rank and sparse matrix decomposition
DRofPCA
- 数据分析类别,使用Java代码实现PCA特征值降维分解-java code PCA dimension reduction eigenvalue decomposition
leifang_V6.2
- Gabor小波变换与PCA的人脸识别代码,matlab开发工具箱中的支持向量机,Pisarenko谐波分解算法。- Gabor wavelet transform and PCA face recognition code, matlab development toolbox support vector machine, Pisarenko harmonic decomposition algorithm.