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conjugategradientmethod.rar
- 给出了线性方程组矩阵Ax=b在并行预处理共轭梯度法求解过程，绝对有用哟,Gives the matrix of linear equations Ax = b in parallel preconditioning conjugate gradient method for solving process, is absolutely useful to yo
Matrixmul
- 求m*n阶实矩阵A与n*k阶实矩阵的乘积矩阵C=A*B-Demand m* n order real matrix A n* k order real matrix product matrix C = A* B
shijuzhenchengfa
- 用于计算两矩阵相乘，在程序运行时输入矩阵A，B的行列数-Used to calculate the two matrices in the program to run when the input matrix A, B the ranks of a few
123
- 高斯列主元素消去法求解矩阵方程AX=B,其中A是N*N的矩阵,B是N*M矩阵 -Out the main elements in Gaussian elimination method for solving the matrix equation AX = B, in which A is N* N matrix, B is N* M matrix
gauss
- 数值分析高斯——列主元消去法主程序 说明如下： ％ a----input,matrix of coefficient ％ b----input,right vector ％ sol----output,returns the solution of linear equation-Gauss numerical analysis- out PCA elimination main program as follows: a---- input, matrix of coeffi
majacobi
- 用Jacobi迭代法解线性方程组Ax=b，A为系数矩阵，b为右端向量-Solution using Jacobi iterative method of linear equations Ax = b, A as the coefficient matrix, b is the right end of the vector
single
- 一般性的奇异值分解算法，float浮点型。-SGGSVD computes the generalized singular value decomposition (GSVD) * of an M-by-N real matrix A and P-by-N real matrix B: * * U*A*Q = D1*( 0 R ), V*B*Q = D2*( 0 R ) * * where U, V and Q are orthogonal matric
single
- 使用奇异值分解来帮助求解最小二乘问题，特别是在方程系数矩阵不满秩的情况下。-SGELSD computes the minimum-norm solution to a real linear least * squares problem: * minimize 2-norm(| b- A*x |) * using the singular value decomposition (SVD) of A. A is an M-by-N * matrix which
maseidelghhhhhhh
- 用途：用Gauss-Seidel迭代法解线性方程组Ax=b 格式：x=maseidel(A,b,x0,ep,N) A为系数矩阵，b为右端向量， -Uses: The Gauss-Seidel iteration method for solving linear equations Ax = b Format: x = maseidel (A, b, x0, ep, N) A as the coefficient matrix, b for the right-hand side vec
2-76
- 求解大型疏松方程组，ap方程组的系数矩阵，b[放回解向量-For solving large loose equations, ap equations coefficient matrix, b [back into the solution vectors
gauss-jakobi
- SOLVING A LINEAR MATRIX SYSTEM AX=B with Gauss Jordan Method
Gauss
- 用全选主元Gauss消去法求解线性方程组。其中a是方程组的系数矩阵，b是右端常数向量，并存放最终解向量，n是阶数。-With full pivoting Gauss elimination method for solving linear equations. Where a is the coefficient matrix, b is the right end of the constant vector, and store the final solution vector, n i
Gauss_Jordan
- 全选主元Gauss-Jordan消去法求解线性代数方程组。其中a是方程组系数矩阵，b先存右端的m组常数向量，之后存解向量。n是阶数，m是右端常数向量组数。-Select the main element Gauss-Jordan Elimination method for solving linear algebraic equations. Where a is the coefficient matrix, b right side of m pre-existing group of c
Levinson
- 采用列文逊递推算法求解对称托伯利兹型方程组。其中t存放T型矩阵的元素。b是右端常数向量。x是解向量。n是阶数。-Using Levinson recursion algorithm for symmetric Tuobolizi equations. Where t T-matrix elements of deposit. b is the right end of the constant vector. x is the solution vector. n is the order.
Strassen
- 设A 和 B 是两个n * n阶矩阵，求它们两的乘积矩阵C。这里，假设n是2的幂次方；-N*N matrix
GaussElimination
- 使用高斯消元法，解线性方程组。写作AX=B型的矩阵形式解决。-Using Gaussian elimination, solution of linear equations. Writing AX = B type of matrix solution.
Gauss_Elimination
- 使用高斯消元法，解线性方程组。写作AX=B型的矩阵形式解决。-Using Gaussian elimination, solution of linear equations. Writing AX = B type of matrix solution.
A_LU
- bool lu(double *a, int *pivot, int n)；矩阵的LU分解。 假设数组an*n在内存中按行优先次序存放，此函数使用高斯列选主元消去法，将其就地进行LU分解。pivot为输出函数.pivot[0,n)中存放主元的位置排列. 函数成功时返回false，否则返回true. bool guass(double const *lu, int const *p, double *b, int n) 求线性方程组的解。 假设矩阵lum*n为某个矩阵a
A_QR
- void qr(double *a, double *d, int n) 矩阵的QR分解 假设数组an*n在内存中按行优先次序存放，此函数使用HouseHolder变换将其就地进行QR分解。 d为输出参数，d[0,n)存放QR分解的上三角矩阵对角线元素。 bool householder(double const *qr, double const *d, double *b, int n) 求线性代数方程组的解。 假设矩阵qrn*n为某个矩阵an*n的QR分解，在内
maxsize
- 稀疏矩阵采用三元组表示。 （1）求两个具有相同行列数的稀疏矩阵A和B的相加矩阵C，并输出C。 （2）求出C的转置矩阵D，输出D。-Sparse matrix expressed by triples. (1) Find the ranks of the two have the same number of sparse matrix A and B of the sum matrix C, and the output C. (2) find the C of the transp