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Description: 人脸识别的程序,通过求特征值来训练预测人脸-face recognition procedure for the adoption of eigenvalues for training forecast to Face
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Size: 232448 |
Author: jys |
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Description: 很好用的有关矩阵的各种操作，包括求逆，特征值，特征向量，svd分解等-good part of the matrix of various operations including inverse, eigenvalues, eigenvectors, svd decomposition, etc.
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Size: 15360 |
Author: 高纯玲 |
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Description: （1）应用9×9的窗口对上述图象进行随机抽样，共抽样200块子图象；
（2）将所有子图象按列相接变成一个81维的行向量；
（3）对所有200个行向量进行KL变换，求出其对应的协方差矩阵的特征向量和特征值，按降序排列特征值以及所对应的特征向量；
（4）选择前40个最大特征值所对应的特征向量作为主元，将原图象块向这40个特征向量上投影，所获得的投影系数就是这个子块的特征向量。
（5）求出所有子块的特征向量。
-(1) the application of 9 × 9 window of these images at random, a total sample of 200 sub-image (2) all sub-images according to out-phase into a 81-dimensional row vector (3) all 200 lines for KL transform vector, derived its corresponding covariance matrix of eigenvectors and eigenvalues, in descending order by eigenvalue and the corresponding eigenvector (4) a choice to 40 corresponding to the largest eigenvalue eigenvector as the PCA, the original image block to the 40 feature vectors on the projection, the projection coefficients obtained by this sub-block eigenvector. (5) calculated for all sub-block eigenvector.
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Size: 64512 |
Author: ly |
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Description: 求特征值的Jacobi法，解决很多工程实际问题-Eigenvalues for Jacobi method to solve many practical problems in engineering
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Size: 2048 |
Author: 天涯 |
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Description: a software code for computing selected eigenvalues of large sparse symmetric matrices
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Size: 7440384 |
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Description: 用雅可比方法求矩阵的特征值和特征向量的FORTRAN程序-Method using Jacobian matrix of eigenvalues and eigenvectors of the FORTRAN program
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Size: 1024 |
Author: 蔡旭晖 |
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Description: GivensHouseholder法求解特征向量和特征值，公司所做项目中就是采用此法求解对称矩阵的特征向量和特征值，仅供参考！-Method GivensHouseholder eigenvector and eigenvalue, the company has done projects that use this method to solve symmetric matrix of eigenvectors and eigenvalues, for reference purposes only!
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Size: 7168 |
Author: cjs |
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Description: 用于计算矩阵的特征值,及矩阵的其他运算.可以用与稀疏矩阵-Used to calculate the matrix of eigenvalues, and other computing matrix. Can be used with the sparse matrix
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Size: 2244608 |
Author: lucia |
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Description: 此为《MATLAB教程》的第八章：特征值和特征向量。该书内容翔实，深入浅出，不可多得。-This is the MATLAB Guide in Chapter VIII: Eigenvalues and eigenvectors. Book is informative, easy, hard to come by.
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Size: 280576 |
Author: 赵远 |
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Description: This function obtains a unitary matrix Q such that: d=diag(Q *diag(lmd)*Q).
In other words, it gives a way to generate a matrix with given eigenvalues and diagonal elements.
By Daniel Perez Palomar (last revision: May 10, 2004).
Feel free to distribute this file as it is (without including any modifications).-This function obtains a unitary matrix Q such that: d=diag(Q*diag(lmd)*Q).
In other words, it gives a way to generate a matrix with given eigenvalues and diagonal elements.
By Daniel Perez Palomar (last revision: May 10, 2004).
Feel free to distribute this file as it is (without including any modifications).
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Size: 1024 |
Author: 马文 |
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Description: PCA算法程序设计步骤：
1、去均值
2、计算协方差矩阵及其特征值和特征向量
3、计算协方差矩阵的特征值大于阈值的个数
4、降序排列特征值
5、去掉较小的特征值
6、去掉较大的特征值(一般没有这一步）
7、合并选择的特征值
8、选择相应的特征值和特征向量
9、计算白化矩阵
10、提取主分量
-PCA algorithm programming steps: 1 to mean 2, calculation of covariance matrix and its eigenvalues and eigenvectors 3, the calculation of covariance matrix eigenvalues greater than the threshold number of 4, in descending order of eigenvalue 5, remove the smaller eigenvalue 6, remove the larger eigenvalue (usually not this step) 7, the combined choice of eigenvalues 8, select the appropriate eigenvalues and eigenvectors 9, computing whitening matrix 10, principal component extraction
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Size: 4096 |
Author: 琴 |
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Description: 基于灰度共生矩阵的纹理特征提取，输出为图像四个方向共十六个特征值-Gray-level co-occurrence matrix based texture feature extraction, the output image in four directions for a total of 16 eigenvalues
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Size: 1024 |
Author: chichen |
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Description: 雅可比迭代（过关法）计算实对称矩阵的特征值和特征向量-Jacobi iteration (immigration law) the calculation of Real Symmetric Matrix Eigenvalues and eigenvectors
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Size: 1024 |
Author: 韦晓辉 |
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Description: Numerical Computing with MATLAB （by Cleve Moler) is a textbook for an introductory course
in numerical methods, Matlab, and technical computing. The emphasis is on in-
formed use of mathematical software. We want you learn enough about the mathe-
matical functions in Matlab that you will be able to use them correctly, appreciate
their limitations, and modify them when necessary to suit your own needs. The
topics include
* introduction to Matlab,
* linear equations,
* interpolation,
* zero and roots,
* least squares,
* quadrature,
* ordinary di?erential equations,
* random numbers,
* Fourier analysis,
* eigenvalues and singular values,
* partial di?erential equations.-Numerical Computing with MATLAB (by Cleve Moler) is a textbook for an introductory coursein numerical methods, Matlab, and technical computing. The emphasis is on in-formed use of mathematical software. We want you learn enough about the mathe-matical functions in Matlab that you will be able to use them correctly, appreciatetheir limitations, and modify them when necessary to suit your own needs. Thetopics include* introduction to Matlab,* linear equations,* interpolation,* zero and roots,* least squares,* quadrature,* ordinary di? erential equations,* random numbers,* Fourier analysis,* eigenvalues and singular values,* partial di? erential equations.
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Size: 3994624 |
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Description: Toolbox for Numerical Computing with MATLAB （by Cleve Moler).
Numerical Computing with MATLAB （by Cleve Moler) is a textbook for an introductory course
in numerical methods, Matlab, and technical computing. The emphasis is on in-
formed use of mathematical software. We want you learn enough about the mathe-
matical functions in Matlab that you will be able to use them correctly, appreciate
their limitations, and modify them when necessary to suit your own needs. The
topics include
* introduction to Matlab,
* linear equations,
* interpolation,
* zero and roots,
* least squares,
* quadrature,
* ordinary di?erential equations,
* random numbers,
* Fourier analysis,
* eigenvalues and singular values,
* partial differential equations.-Toolbox for Numerical Computing with MATLAB (by Cleve Moler). Numerical Computing with MATLAB (by Cleve Moler) is a textbook for an introductory coursein numerical methods, Matlab, and technical computing. The emphasis is on in-formed use of mathematical software. We want you learn enough about the mathe-matical functions in Matlab that you will be able to use them correctly, appreciatetheir limitations, and modify them when necessary to suit your own needs. Thetopics include* introduction to Matlab,* linear equations,* interpolation,* zero and roots,* least squares,* quadrature,* ordinary di? erential equations,* random numbers,* Fourier analysis,* eigenvalues and singular values,* partial differential equations.
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Size: 243712 |
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Description: 通过数值计算的方法依次改变本征值的取值，然后计算出相应的波函数。-By numerical calculation in order to change the values of eigenvalues, and then calculate the corresponding wave function.
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Size: 1024 |
Author: haolee |
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Description: 如何利用MATLAB求最小特征值和特征向量,并将特征向量归一化-How to use MATLAB for the smallest eigenvalues and eigenvectors, and the normalized eigenvector
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Size: 3072 |
Author: zp |
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Description: 反幂法求矩阵的特征值和特征向量
反幂法适用于矩阵的按模最小的特征值和对应的特征向量。
使用说明：
一般的使用过程：
1、修改输入数据 input2.txt
2、编辑源文件 fanmifa.c
3、编译程序 fanmifa.bat
4、运行 fanmifa.exe
-Anti-power-law matrix eigenvalues and eigenvectors inverse power law applies to the modulus matrix by the smallest eigenvalues and corresponding eigenvectors. Usage: the use of the general process: 1, modify the input data input2.txt 2, edit the source file fanmifa.c3, compiler fanmifa.bat4, running fanmifa.exe
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Size: 263168 |
Author: |
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Description: 雅克比方法求矩阵的特征值和特征向量，matlab文件，已经调试成功了-Methods for Jacobian matrix eigenvalues and eigenvectors, matlab documentation, debugging has been successful
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Size: 1024 |
Author: lily |
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Description: 包括使用修正Gram-Schmit算法实现QR分解，自编LU分解、利用幂法和反幂法计算矩阵最大和最小特征值的程序。例外附有使用这些算法的例子供参考。 QR decomposition algorithm based on modified Gram-Schmit LU decomposition algorithm algorithm used to find maximum and minimum eigenvalue based on power and inverse power method and some examples are also included.-Including the use of Gram-Schmit amended QR decomposition algorithm, self-LU decomposition, the use of power law and inverse power method to calculate maximum and minimum matrix eigenvalue procedures. With the exception of the examples of the use of these algorithms for reference. QR decomposition algorithm based on modified Gram-Schmit LU decomposition algorithm algorithm used to find maximum and minimum eigenvalue based on power and inverse power method and some examples are also included.
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Size: 4096 |
Author: gogomx |
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