搜索资源列表
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
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
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.
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
Gaussian--and-LU
- 计算方法中解线性方程组的列主元高斯消元法及LU分解，由键盘输入系数矩阵A的大小和内容、及矩阵b的内容-Calculation methods listed in the main solution of linear equations Gaussian elimination method and LU decomposition, the coefficient matrix A by the keyboard input size and content, and the content
FRACTIONAL_DIFFERINTEGRAL
- 通过傅里叶扩展计算的微分和积分函数，十分有用。-Descr iption The n-th order derivative or integral of a function defined in a given range [a,b] is calculated through Fourier series expansion, where n is any real number and not necessarily integer. The necessa
CeShi2
- 已知复数矩阵A求A的逆矩阵B，这个过程比较复杂。- finding the inverse matrix
Gseidel
- Main program with a data file for the resolution of a system Ax=b The data file contents the dimension n and the values of the matrix A and the vector b.
LU2
- Method of resolution system Ax=b with a LU method. The program needs a data file, for reading the values of the components of the matrix A and the vector b.
arnoldi-decomposition
- Alnoldi decomposition of matrix used for computing AX =b solution
ok
- 以字符形式打开文件 其中x.txt是数据文件 16进制转化为10进制数，存入alpha矩阵 将得出数据存入新的b.txt文档 - Open the file in characters which are data files x.txt hexadecimal to decimal conversion, alpha matrix deposit will yield data into a new document b.txt
Cholesky-decomposition
- 实对称正定矩阵的 的Cholesky分解.用平方根法和改进的平方根方法求解线性方程组 Ax=b. -Real symmetric positive definite matrix of the Cholesky decomposition method and improved by the square root of the square root method for solving linear equations Ax = b.
LSQR-NNL
- 可用于求解超大规模线性方程组非负解的MATLAB函数-Given a tall full-rank matrix A, solves the nonnegative least squares problem: min ||Ax-b|| s.t. x>= 0 and returns the minimizer x. The argument err is the tolerance used in testing for zeros
BCMUL
- 求m*n阶直矩阵A与n*k阶重短阵B的乘积矩阵C= AB-Find m* n-order linear matrix A and n* k matrix B short-order heavy product matrix C = AB
BRMUL
- 求m*n阶矩阵A与n*k阶矩阵B的乘积短阵.-Find m* n order matrix A and n* k matrix B short order matrix multiplication of.
2013082711183910
- 对于由n个未知数，n个方程组成的组多元一次方程组： a11X1+a12X2+．．．+a1nXn = b1 a21X1+a22X2+．．．+a2nXn = b2 ．．．．．． an1X1+an2X2+．．．+annXn = bn 写成矩阵形式为Ax=b，其中A为系数n*n方阵，x为n个变量构成列向量，b为n个常数项构成列向量。当它的系数矩阵可逆，或者说对应的行列式|A|不等于0的时候，由Ax=b可得：x=b*A-1 ，A-1为A的逆矩阵。-For the group consi
k
- 用K均值聚类分析把多组数据分成两类 本程序为给定20组数据（用矩阵A表示）分成B、C两组。-K-means clustering analysis of the multiple sets of data into two categories This program is given 20 sets of data (represented by the matrix A) into B, C groups.
SolveLinearEqutations
- 全选主元高斯-约当消去法求解稀疏线性方程组 输入参数a[]系数矩阵，n线性方程阶数，b[]右端项 输出参数b[]方程组的解 返回值 ： 1求解成功 0求解失败-Select the main element Gauss- Jordan elimination method for solving sparse linear equations Input parameters a [] coefficient matrix, n order linear equations, b