搜索资源列表
Decomposition_LU
- 将系数矩阵A转变成等价两个矩阵L和U的乘积 ,其中L和U分别是下三角和上三角矩阵。当A的所有顺序主子式都不为0时,矩阵A可以唯一的分解为A=LU。其中L是单位下三角矩阵,U是上三角矩阵。 -The coefficient matrix A into two matrices L and U is equivalent to the product, where L and U are lower triangular and upper triangular matrix. When A mas
Decomposition_QR
- QR分解法是三种将矩阵分解的方式之一。这种方式,把矩阵分解成一个正交矩阵与一个上三角矩阵的积。QR 分解经常用来解线性最小二乘法问题。QR 分解也是特定特征值算法即QR算法的基础。-QR decomposition are the three ways of decomposition of the matrix. In this way, the matrix decomposition into an orthogonal matrix and an upper triangular mat
Gauss-Decom
- 用matlab实现矩阵的高斯分解,A=LU,A为下三角,U为上三角-Gauss decomposition
Lu
- 数值计算中的LU分解法的实现算法,将矩阵分解为上三角和下三角矩阵进行运算-LU code
FindSealRect
- 各种突出顔色定位与分形算法。可实现圆,三角,楕圆,四边形等分解-Prominent location and color of various fractal algorithms. Can achieve a round, triangular, FREQUENCY round, rectangular and other decomposition
cholesky
- Cholesky分解是一种分解矩阵的方法, 在线形代数中有重要的应用。Cholesky分解把矩阵分解为一个下三角矩阵以及它的共轭转置矩阵的乘积(那实数界来类比的话,此分解就好像求平方根)。与一般的矩阵分解求解方程的方法比较,Cholesky分解效率很高-Cholesky decomposition is a kind of decomposition of matrix method, the linear algebra has an important application. Choles
LUdecomposition
- 数值分析中,求解线性方程。可以将矩阵分解为下三角和上三角矩阵的乘积-Numerical analysis, it is used for solving linear equations. The matrix will be decomposed into the product of lower triangular matrices and upper triangular matrices
QRdecomposition
- 矩阵分解的一种方式。把矩阵分解成一个正交矩阵与一个上三角矩阵的积-One way for matrix decomposition.Matrix will be decomposed into the product of an orthogonal matrix and an upper triangular matrix
SQR-Decomposition-C-code
- 将矩阵按照列向量的模从小到大排序并分解为一个正交矩阵与一个上三角矩阵乘积形式。-The matrix according to the column vector of the mode from small to large and decomposes as an orthogonal matrix and an upper triangular matrix product form.
Solving-linear-equations
- 数值计算第二章编程作业:高斯顺序消元法、列选主元、三角分解法(Doolittle分解、Crout 分解)、全选主元、平方根法、追赶法解线性方程组-Order Gaussian elimination method, column pivoting, triangular decomposition (Doolittle, decomposition, decomposition Crout s), Select the main element, the square root of the
test
- 实对称正定矩阵LDL^分解,其中L为单位下三角矩阵,D为对角阵-A recursive algorithm for calculating the eigenvalues of a real symmetric matrix based on LDLT decomposition is given. With this algorithm, the number of eigenvalues of a real symmetric matrix in the given interval c
test
- 实对称正定矩阵LD和UD分解,即A=LDL^或A=UDU^,其中L为单位下三角矩阵,U为单位上三角矩阵,L^和U^分别是L和U的转置矩阵,代码自己写的,C++,学工科的同学可能会用到这两个分解,算法也有,可以-Real symmetric positive definite matrix LD and UD decomposition, that is A = LDL^ = UDU ^ where L is unit lower triangular matrix, U as a unit t
Bee22md2mE
- BEMD对图像进行分解,包络构造使用Delaunay三角剖分与三次插值,的的到分解的结果。输入:灰度bmp图像输出:imf1 imf2 imf3 残差 -BEMD decomposition of the image, envelope constructed using the Delaunay triangulation with cubic interpolation of the result of decomposition. Input: grayscale bmp image
source-code
- 五个Fortran程序,分别给出了三角方程组、高斯消去法、选主元消去法、Crout分解、Doolittle分解的程序源代码,给出了驱动函数,适于初学者学习-Five Fortran programs, respectively trigonometric group, Gaussian elimination, pivoting elimination, Crout decomposition, Doolittle, decomposition of the source code gives
LDLUDU
- Doolittle分解,Q=L*R,L是单位下三角;UDU 分解,U是单位上三角阵.Doolittle分解,Q=L*R,L是单位下三角;LDL 分解,L是单位下三角阵(下*对*上)-Doolittle decomposition Q = L* R, L is unit lower triangular UDU ' decomposition, U is the unit upper triangular matrix. Doolittle, decomposition, Q = L* R
C-Program-examples
- 河内塔 费式数列 巴斯卡三角形 三色棋 老鼠走迷官(一) 老鼠走迷官(二) 骑士走棋盘 八个皇后 八枚银币 生命游戏 字串核对 双色、三色河内塔 背包问题(Knapsack Problem) 数、运算 蒙地卡罗法求 PI Eratosthenes筛选求质数 超长整数运算(大数运算) 长 PI 最大公因数、最小公倍数、因式分解 完美数 阿姆斯壮数 最大访客数 中序式转
LUfact
- LU分解,通过A=LU将矩阵分为上三角和下三角-LU decomposition A = LU matrix into upper triangular and lower triangular
program
- 矩阵DLU分解,A=D+L+U,D为对角矩阵,L为下三角矩阵,U为上三角矩阵-Matrix DLU decomposition
shuzhifenxi2
- 对矩阵拟上三角化,并且对矩阵进行QR分解,从而求出矩阵的特征值以及特征向量。-Matrix intend on triangulation, and matrix QR decomposition, and thus find the eigenvalues and eigenvectors of the matrix.
ldu
- 将一个稀疏矩阵分解因子,构成上三角矩阵,对角矩阵和下三角矩阵相乘的形式。即LDU分解。-Factoring a sparse matrix, constitute the upper triangular matrix, in the form of a diagonal matrix and lower triangular matrix multiplication. That LDU decomposition.