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Description: 1、随机生成一个5*5矩阵A，元素符合均匀分布；再随机生成一个5*5矩阵B，元素符合正态分布。对A和B进行加、减、乘、除、比较等矩阵运算，查看运算结果。
2、创建5阶魔术矩阵，求A的行列式、特征值、逆、秩、迹、条件数。
3、假设矩阵 ，求A的LU分解、正交分解、特征值分解、奇异值分解。
4、创建6阶单位稀疏矩阵，并显示其全部元素。
-1, randomly generated a 5* 5 matrix A, elements in line with uniform distribution then randomly generated a 5* 5 matrix B, elements in line with normal distribution. Pairs of A and B to add, subtract, multiply, divide, comparison matrix operations, view the results of operations. 2, create a 5-order magic matrix, find A, determinant, eigenvalues, inverse, rank, trace, the condition number. 3, assuming that matrix, find A, LU decomposition, orthogonal decomposition, eigenvalue decomposition, singular value decomposition. 4, create a six-order unit of sparse matrix, and display all of its elements.
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Size: 2048 |
Author: zhu |
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Description: 1.对一个256*256的图像进行DCT变换得到图像D，将D得斜下角数值置为零，然后进行DCT反变换.
2.对源图像进行K-L转换
1和2比较-1.Get a grey level image which size is N*N. (For example, 256*256, however,
N = ), and partition to 8*8 sub images.
2.. Apply DCT to these sub images, and get the transformed image D with DCT
coefficients for elements.
3. From D, keep the coefficient values for only upper left triangular region and set
zeros for lower right region to approximate the image. (That is, only half of data
is used.)
4.Take Inverse DCT to get the approximated image.
2 . Get the covariance matrix of image.
3 . Calculate the corresponding eigenvectors and eigenvalues.
4 . Represent the original image with Singular Value Decomposition.
5 . Approximate the image by taking off the 4 smallest eigenvalues. (That is, only
half of information is used.)
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Size: 1024 |
Author: zhengyan |
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Description: 实对称矩阵特征值与特征向量的雅克比法，ap为是对称矩阵，vp返回特征向量-Real Symmetric Matrix Eigenvalues and Eigenvectors of the Jacobian method, ap is a symmetric matrix, vp return eigenvector
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Size: 39936 |
Author: kaidu |
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Description: 本程序为求矩阵的最大特征值、全部特征值和特征向量，应用乘幂法和雅可比过关法-This procedure for the sake of the largest eigenvalue matrix, all eigenvalues and eigenvectors, applications by a power law and the Jacobi clearance method
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Size: 2048 |
Author: 源治 |
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Description: 该程序可以测试人脸的二维的区间矩阵的稳定性。详细说明见英文说明-The program can test the stability of 2-D face of an interval matrix.
By relying on a two-dimensional (2-D) face test, Ref [1,2] obtained a necessary and sufficient condition for the robust Hurwitz and Schur stability of interval matrices. Ref [1,2] revealed that it is impossible that there are some isolated unstable points in the parameter space of the matrix family, so the stability of exposed 2-D faces of an interval matrix guarantees stability of the matrix family. This program provides the examples to demonstrate the applicability of the robust stability test of interval matrices in Ref [1, 2].
Remarks:
(1) The 2-D face of an interval matrix is Hurwitz stable, if and only if the maximum real part of the eigenvalues of the 2-D face of the interval matrix is smaller than 0 [1].
(2) An interval matrix is Hurwitz stable, if and only if all the 2-D faces of the interval matrix is Hurwitz stable.
(3) The 2-D face of an interval matrix is Schur stable, if and only if the maxi
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Size: 3072 |
Author: Hao Wang |
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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
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Size: 148480 |
Author: alice |
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Description: 用幂法和反幂法实现求矩阵的特征值和特征向量-With the power method and inverse power law to achieve demand matrix eigenvalues and eigenvectors
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Size: 1024 |
Author: zhaolong |
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Description: IRBLEIGS: Finds a few eigenvalues and eigenvectors of a Hermitian matrix.
IRBLEIGS will find a few eigenvalues and eigenvectors for either the standard eigenvalue problem A*x = lambda*x or the generalized eigenvalue problem A*x = lambda*M*x, where A is a sparse Hermitian matrix and the matrix M is positive definite.
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Size: 15360 |
Author: Judy |
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Description: Characteristic polynomial, eigenvalues, eigenvectors
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Size: 1024 |
Author: katore vishal |
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Description: Graphical demonstration of eigenvalues and singular values
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Size: 2048 |
Author: katore vishal |
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Description: Eigenvalues and their algebraic multiplicity.
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Size: 1024 |
Author: katore vishal |
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Description: Eigenvalues and eigenvectors of a normal matrix A.
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Size: 1024 |
Author: katore vishal |
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Description: Eigenvalues and eigenvectors of a symmetric matrix.
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Size: 1024 |
Author: katore vishal |
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Description: 摘要：主成分分析（PCA）的人脸识别算法，以减少的特征向量是涉及到对抽象的特点，改进了主成分分析（一）iUumination算法的变化影响酶原sed.The方法是基于上减低与正常化其相应的标准差的特征向量元素相关联的大特征值的特征向量的影响力的想法。耶鲁大学和耶鲁大学面临的数据库面对数据库B是用来验证-Abstract：In principal component analysis(PCA)algorithms for face recognition，to reduce the influence of the
eigenvectors which relate to the changes of the iUumination on abstract features，a modified PCA ( A)
algorithm is propo sed．The method is based on the idea of reducing the influence of the eigenvectors associated
with the large eigenvalues by normalizing the feature vector element by its corresponding standard deviation．
Th e Yale face database and Yale face database B are used to verify the method．The simulation results show
that，f0r front face and even under the condition of limited variation in the facial po ses the proposed method
results in better perform ance than the conventional PCA and linear discriminant analysis(LDA)approaches．and
the computational cost remains the same as that ofthe PCA，and much less than that ofthe LDA．
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Size: 205824 |
Author: 费富里 |
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Description: 这是一个关于求矩阵特征值的matlab程序，程序简单命了，注有说明，能够实际运用-This is a demand matrix eigenvalues on the matlab program, procedures are simple life, and note there are instructions to the practical application of
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Size: 3072 |
Author: 张楠 |
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Description: 比较深入的分析了PCA人脸识别方法的原理，并对PCA在应用过程中遇到的特征值选择和距离准则问题进行了研究，实现了基于PCA算法的人脸识别。-More in-depth analysis of the principle of PCA face recognition method, and in the application of PCA eigenvalues encountered in the course selection and distance criteria conducted a study to achieve face recognition algorithm based on PCA.
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Size: 5434368 |
Author: 夏天 |
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Description: Jocobi算法，计算矩阵的特征向量和特征值。-Jocobi algorithm, computing matrix eigenvectors and eigenvalues.
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Size: 1358848 |
Author: tang |
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Description: MATLAB 数值计算 入门 源码
² introduction to MATLAB
² linear equations
² interpolation
² zero ¯ nding
² least squares
² quadrature
² ordinary di® erential equations
² random numbers
² Fourier analysis
² eigenvalues and singular values
² partial di® erential equations-Numerical Computing with MATLAB
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Size: 251904 |
Author: hanklynn |
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Description: A program for the calculation of energy eigenvalues and eigenstates of a Schrodinger equation
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Size: 5120 |
Author: peterye |
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Description: Two computer programs for solving the Schrodinger equation for bound state eigenvalues and eigenfunctions using the Fourier Grid Hamiltonian
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Size: 9216 |
Author: peterye |
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