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lusolvec
- lusolvec.f Numerical solution of a set of linear C *** Equations / a matrix equation A * x = b C *** using LU decomposition, matrix A and C *** vectors b and x being double complex, C *** and inversion of A.-3-D FDTD code with PEC
GaussianElimination
- x=GaussianElimination(A,b) GaussianElimination solves system of linear equations of the form Ax = b using Gaussian Elimination method. A = n x n square matrix with the coefficients of the system of equations as the elements of matrix A b
Gauss
- 高斯列主元解方程组，子程序，对应矩阵A，b，即可求解x-The Gaussian main-element solution of equations, subroutine, the corresponding matrix A, b, to solve for x
G-S
- 本程序为G-S迭代法，若系数矩阵满足 1.G-S迭代矩阵谱半径小于一 2.jacobi迭代矩阵一范数或无穷范数小于一 3.系数矩阵A正定 4.系数矩阵A严格对角占优或不可约对角占优 则可返回A*x=b的解。算法迭代次数比 x=M*x+g形式的标准化迭代次数多，但所用时间少很多。-The program for the G-S iteration method, if the coefficient matrix 1.G-S iterative matrix spect
Incremental-SVD-updates
- 增量奇异值分解算法，来至MIT大学的wingate教授，含3个源码.-Given the thin SVD of a matrix (X=USV ), update it in a number of interesting ways, while preserving the rank of the result. svd_update.m- update the SVD to be [X+ A *B]=Up*Sp*Vp (a general matrix update). add
region-match
- 图像的区域匹配，输入：两幅图像分割之后的邻接矩阵，还有两幅图像分割区域的每个块之间的相似度，就可以得出区域一对一匹配的关系-region match input：Adjacency matrix of picture A,B and Affinity matrix represent the Affinity of the every regions between pictures output:one-to-one match between regions of two pictu
shuxuemoxing
- 1,某厂向用户提供发动机，合同规定，第一、二、三季度末分别交货40台、60台、80台．每季度的生产费用为 f=ax+bx^2（元），其中x是该季生产的台数．若交货后有剩余，可用于下季度交货，但需支付存储费，每台每季度c元．已知工厂每季度最大生产能力为100台，第一季度开始时无存货，设a=50、b=0.2、c=4，问工厂应如何安排生产计划，才能既满足合同又使总费用最低． 2,函数的输入为A,B两个矩阵，实现如下功能：从A矩阵中找出与B完全相同的子矩阵，并将该子矩阵左上角的位置保存到2*n的向量
New-WinRAR-archive
- the codes are mearnt for solving linear equations of the form Ax= b where A is a matrix
GAUSSJ
- 线性方程组的解法 全主元高斯－约当(Gauss-Jordan)消去法 用高斯－约当消去法求解A[XY]=[BI]，其中A为n*n非奇异矩阵，B为n*m矩阵，均已知；X(n*m)，Y(n*n)未知。-Solution of linear equations the main yuan Gaussian- Jordan (Gauss-Jordan) elimination method Gauss- Jordan elimination method to solve A [XY] = [B
LUDCMP
- 解线性方程组 LU分解法 求解系数矩阵为非奇异的线性代数方程组Ax=b,它能串联式地逐次解A相同b不同的方程组。本方法也叫杜利特尔(doolittle)方法-Linear Equations LU decomposition method for solving non-singular coefficient matrix of linear algebraic equations Ax = b, it cascaded to the same b successive solutio
kmeans1
- K-means算法，算法步骤如下： Step1.利用式(2)计算距离矩阵D=()，其中=dist[i, j] ()； Step2.扫描坐标距离矩阵D，寻找距离的最大值和最小值，用式(3)计算limit； Step3.扫描坐标距离矩阵D，寻找矩阵中距离最小的2个数据a，b，将数据a，b加入集合，={a,b}，同时将数据a，b从U中删除，更新距离矩阵D； Step4.利用 (4)式在U中寻找距离集合最近的数据样本t，如果小于limit，则将t加入集合，同时将t从集合U中删除，更新
juzhenchufa
- 计算矩阵的除法，形如A*x=b，其中A为n*n的方矩阵，b为列矩阵-Division of the matrix calculation, shaped like A* x = b, in which A square matrix for n* n, b for the column matrices
ACJDN
- 用全选主元高斯-约当消去法求解系数矩阵相同而具有多组右端常 数向量的复系数线性代数方程组AX=B-PCA Gaussian with Select- Jordan elimination method for solving the same coefficient matrix and constant vector with multiple groups of the right end of the complex coefficients of linear algebraic e
gmres
- gmres 方法。视图求解线性方程组A*x=b的解x。nXn的稀疏矩阵A必须是方程且应是大型稀疏矩阵。列向量b的长度必须为n。-gmres method. View solving linear equations A* x = b the solution x. nXn sparse matrix A must be equation and should be large sparse matrix. The length of the column vector b must be to
gauss
- 高斯消去法求解AX=b，利用对增广矩阵进行的初等行变换，将系数矩阵变为上三角矩阵，然后回带，可以得到方程组的解。-Gaussian elimination method for solving AX = b, using the augmented matrix for the elementary row transformation, the coefficient matrix into an upper triangular matrix, and then back to the ta
jacobi
- 对于方程组AX=b，当系数矩阵非奇异时，对原方程进行改写，利用公式X^k=BX^(k+1)+g进行迭代求解。-For equations AX = b, when the coefficient matrix is nonsingular, rewriting the original equation, using the formula X ^ k = BX ^ (k+1)+g for iterative solution.
Video-display-and-read-write
- MATLAB 最常處理的影像格式為索引影像（Indexed Images） 顯示此類型影像的語法如下： image(X) colormap(map) 其中X為影像的資料矩陣，map為色盤矩陣。 色盤矩陣的大小為K×3，每個橫列由三個元素所組成，分別是R（紅） 、G（綠）、B（藍） ，每個元素的範圍為0~1 X的值為1~K，也就是當X(i, j)的值為p，則像素點(i, j) 的顏色為map(p, :)這一列的值所決定。 -MATLAB image forma
dc
- DC Defect Correction Method. X = DC(A,B) attempts to solve the system of linear equations A*X = B for X. The N-by-N coefficient matrix A must be square and the right hand side column vector B must have length This uses the defect correctio
CGMethod
- 该方法给出了一个CG算法求对称正定矩阵的线性方程的解，要求给出矩阵A、向量b和一个探测向量x0。-This method gives a CG algorithm for linear equations of symmetric positive definite matrix, requiring to give a matrix A, a vector b and a probe vector x0.
ALDLE
- 高斯-赛德尔迭代法 用高斯-赛德尔迭代法求解系数矩阵具有主对角线占绝对优势的线性代数方程AX=B-Gauss- Seidel iterative method with Gauss- Seidel iterative method for solving the coefficient matrix has a dominant main diagonal linear algebraic equations AX = B