Description: Maximum eigenvalue and the corresponding eigenvector.-Maximum and the corresponding eigenvalue eigenvector. Platform: |
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Author:金岳 |
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Description: 矩阵的转置、行列式、秩，逆矩阵求法，矩阵的三角分解、qr分解，对称正定矩阵的乔里斯基分解及行列式值，奇异值分解，广义逆的奇异值分解，矩阵特征值与特征向量的各种计算方法-all kinds of computational method of transposition of matrix, determinant, rank, inverse of matrix,triangle decomposition, qr decomposition, cholesky decomposition and determinant value based on symmetry positive definite matrix, decomposition of singular value, decomposition of generalized inversal singular value, eigenvalue and eigenvector Platform: |
Size: 82944 |
Author:球球 |
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Description: 幂法求矩阵的特征值和特征向量
算法9.1
1． 输入矩阵A，初始向量X，误差限ε最大迭代次数N。
2． 置k=1，u=0。
3． 求xr=>λ，|xr|=max|xr|,i=1,….,n。
4． 计算
Y=X/λ，X=AY
5． 若|λ-u|〈ε，输出λ，X，停机；否则，转步骤6。
6. 若k<N，k+1=>k，λ=>u,转步骤3；否则，输出错误信息，停机
-Power-law matrix eigenvalue and eigenvector algorithm 9.11. Input matrix A, the initial vector X, the error ε maximum iteration limit N. 2. Home k = 1, u = 0. 3. For xr => λ, | xr | = max | xr |, i = 1, ...., N. 4. Calculation Y = X/λ, X = AY5. If | λ-u | <ε, the output λ, X, downtime Otherwise, switch to step 6.6. If k <N,k+1=> k, λ => u, to Step 3 Otherwise, output an error message , parking Platform: |
Size: 18432 |
Author:Gellss |
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Description: Maximum eigenvalue and the corresponding eigenvector.-Maximum and the corresponding eigenvalue eigenvector. Platform: |
Size: 1024 |
Author:金岳 |
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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. Platform: |
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Author:ly |
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Description: 本程序采用fortran编写，为用Jacobi法求实对称矩阵的特征值与特征向量-This procedure using fortran prepared for the Jacobi method using realistic symmetric matrix eigenvalue and eigenvector Platform: |
Size: 1024 |
Author:qwe |
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Description: 1． Using power method to find the eigenvalue with maximum modulus and its eigenvector for the following matrixes-1. Using power method to find the eigenvalue with maximum modulus and its eigenvector for the following matrixes Platform: |
Size: 84992 |
Author:吕鹏 |
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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! Platform: |
Size: 7168 |
Author:cjs |
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Description: 幂法是一种计算矩阵主特征值（矩阵按模最大的特征值）及对应特征向量的迭代方法，特别适用于大型稀疏矩阵。
但是，一般幂法迭代向量v的各个不等于零的分量将随k 趋向于无穷大而使计算机溢出。因此，我们必须对某通幕法进行规范。即规范化幂法
-Power Method is a calculation of the main eigenvalue matrix (matrix according to the largest eigenvalue modulus) and the corresponding eigenvector of the iterative method, especially for large sparse matrix. However, the general power-law iteration vector v is not equal to zero all the components will be as k tends to infinity overflow of the computer. Therefore, we must pass a law to regulate screen. That is, standardized Power Method Platform: |
Size: 12288 |
Author:knight |
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Description: 使用C++语言实现主成分变换算法pca，包含求特征值特征向量-The use of C++ Language realize the principal component transform algorithm pca, contains eigenvector for eigenvalue Platform: |
Size: 5120 |
Author:海礁 |
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Description: Probabilistic Principal Components Analysis. [VAR, U, LAMBDA] = PPCA(X, PPCA_DIM) computes the principal
％ component subspace U of dimension PPCA_DIM using a centred covariance
matrix X. The variable VAR contains the off-subspace variance (which
is assumed to be spherical), while the vector LAMBDA contains the
variances of each of the principal components. This is computed
using the eigenvalue and eigenvector decomposition of X.-Probabilistic Principal Components Analysis. [VAR, U, LAMBDA] = PPCA (X, PPCA_DIM) computes the principal component subspace U of dimension PPCA_DIM using a centred covariancematrix X. The variable VAR contains the off-subspace variance (whichis assumed to be spherical ), while the vector LAMBDA contains thevariances of each of the principal components. This is computedusing the eigenvalue and eigenvector decomposition of X. Platform: |
Size: 1024 |
Author:西晃云 |
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Description: 常用算法的C程序。主要内容包括多项式的计算、复数运算、随机数的产生、矩阵运算、矩阵特征值与特征向量的计算、线性代数方程组的求解、非线性方程与方程组的求解、插值与逼近、数值积分、常微分方程组的求解、数据处理、极值问题的求解、数学变换与滤波、特殊函数的计算、排序和查找。-Commonly used algorithm of C procedures. Include polynomial terms, complex computation, random number generation, matrix operations, matrix eigenvalue and eigenvector calculations, linear algebra equations, nonlinear equations with the equations, interpolation and approximation, numerical integration, solving ordinary differential equations, data processing, for solving extremum problems, mathematical transformation and filtering, the calculation of special functions, sorting and search. Platform: |
Size: 13312 |
Author:周泽华 |
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Description: 计算机常用数值计算算法与程序(C++),主要用于科学计算中的复数运算，多项式与连分式计算，矩阵运算，矩阵特征值与特征向量的计算，线性方程组求解，非线性方程(组)求解，插值，数值积分，常微分方程(组)求解，数值拟合与逼近，数据处理与回归分析，极值等。
-Commonly used computer algorithms and numerical procedures (C++), Mainly used for scientific computing complex in the computation, polynomials and continued fractions calculation, matrix operations, matrix eigenvalue and eigenvector calculation, solving linear equations , non-linear equation (group) to solve, interpolation, numerical integration, ordinary differential equations (group) to solve, numerical simulation and approximation, data processing and regression analysis, extreme value, etc.. Platform: |
Size: 216064 |
Author:范高杰 |
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Description: 矩阵的本征值以及本征向量求解的数值程序，包括QR方法，householder方法等-Matrix eigenvalue and eigenvector of the numerical solving procedures, including the QR method, householder methods Platform: |
Size: 2437120 |
Author:叶飞 |
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Description: 矩阵的特征值与特征向量
（1）理解矩阵的特征值、特征向量的基本概念；了解矩阵特征多项式概念；
（2）熟练掌握求矩阵的特征值、特征向量的方法；
（3）掌握矩阵的特征值和特征向量的基本性质；
（4）了解求矩阵特征值和特征向量的MATLAB 和MAPLE 命令-Matrix Eigenvalues and eigenvectors (1) understand the matrix eigenvalues, eigenvectors of the basic concepts understanding of the concept of matrix characteristic polynomial (2) proficiency in order to matrix eigenvalue, eigenvector method (3) control Matrix eigenvalues and eigenvectors of the fundamental nature (4) Understanding the demand matrix, eigenvalues and eigenvectors of MATLAB and MAPLE commands Platform: |
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Author:alice |
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Search - eigenvalue eigenvector