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实验5-雅可比迭代
- 用Matlab软件以及雅克比迭代和高斯－赛德尔迭代解方程组Ax=b，分析、比较其结果-using Matlab software and the iterative and Jacques than Gauss - Seidel iterative solution equations Ax = b, analysis, comparison of the results
matlab-code
- matlab解线性方程组的源代码 function x=nagauss2(a,b,flag) ％ 用途：选列主元Gauss消去法解线性方程组ax=b ％ 格式：x=nagauss2(a,b,flag) a为系数矩阵，b为右端列向量，flag若为0，则显示中间过程 -Matlab solution of linear equations source code function nagauss2 x = (a , b, flag)% purposes : a selection P
EOM
- 拉格朗日插值多项式拟合,牛顿插值多项式,欧拉方程解偏微分方程,使用极限微分求解导数（微分）,微分方程组的N=4龙格库塔解法,雅可比爹迭代法解方程AX=B,最小二乘多项式拟合,组合辛普生公式求解积分,用三角分解法解方程AX=B-Lagrange interpolation polynomial fitting, polynomial interpolation Newton, Euler equations partial differential equations, Limit the use
Gauss
- 解n阶线形方程组Ax=b的列主元高斯消去法的通用程序如下(下列程序都是在 matlab平台下编写的)
数字图像处理Matlab编程
- 本程序是对一幅图像进行变灰度、旋转、锐化、在图像上画圆或椭圆、直线等操作的程序。 说明：要实现相应功能的操作，需要在输入框内输入正确的表达式。举例如下： 画直线：x1=20,y1=15,x2=150,y2=100 画圆：x=100,y=100,r=20 画椭圆：x=100,y=100,r=20,a=16,b=9 旋转：x=30(度数)，ax=100,ay=90 锐化：x=80-this procedure is a gray image change, rotation, sharpening
guass 高斯消去法求解线性方程组
- 高斯消去法求解线性方程组 输入变量为一个n阶非奇异方阵A，和n维列向量b，输出的结果为线性方程组Ax=b的解-Gaussian elimination method for solving linear equations
TVCMRI_pub.zip
- matlab code for Fixed point and Bregman iterative methods. minimize alpha*TV(Phi *x) + beta*||x||_1 + 0.5*||Ax-b||_2^2 ,matlab code for Fixed point and Bregman iterative methods. minimize alpha*TV(Phi*x)+ beta*||x||_1+ 0.5*||Ax-b||_2^2
compress edsensing OMP
- 压缩感知 正交匹配追踪一些人关心压缩感知与雷达成像，他们把稀疏表示放在最重要的地方，以为在雷达成像中成功实现压缩感知关键是稀疏表示； 事实上并不是如此。我们知道：压缩感知需要建立AX=B,且该方法具有较低的抑制信噪比能力；另外雷达成像的基础是雷达 信号与目标的相互作用，也就是电磁波与介质的相互作用，该相互作用是一个非常复杂的非线性问题，因此研究这个问题与 压缩感知的关系才是解决雷达成像问题的关键点所在。从另外一个角度来看，雷达成像中惯用的方法是匹配滤波，
lsqr_b
- 此算法为用于解反问题的lsqr算法，对Ax=b，输入矩阵A，列向量b，以及迭代步数，求得列向量x-This algorithm is used for solution of the inverse problem lsqr algorithm, Ax = b, the input matrix A, the column vector b, as well as the number of iterative steps, to seek the column vector x
preconjgrad
- preconjgrad：预处理共轭梯度法求线性方程组Ax=b的解 conjgrad：共轭梯度法求线性方程组Ax=b的解 twostep:两部迭代法求线性方程组Ax=b的解 fastdown:快速下降法求线性方程组Ax=b的解-preconjgrad: preconditioned conjugate gradient method for solving linear equations Ax = b solution conjgrad: conjugate gradient met
equation
- 分别用高斯消去法，三角分解法，Jacobi迭代法，GS迭代法，SOR迭代法求解Ax=b-Separately using Gaussian elimination, triangular decomposition, Jacobi iterative method, GS iterative method, SOR iterative method for solving Ax = b
Gauss_elimination
- Gauss Elimination Algorithm is used to solve linear equations in the form Ax=B, find rank of matrix and to find inverse of matrixes. The program is done in matlab platform.
art
- 用于解反问题的代数重建法，对于Ax=b，输入矩阵A，列向量b，以及迭代步数k，可求的列向量x-Algebraic solution of the inverse problem for the reconstruction of France, for Ax = b, the input matrix A, the column vector b, as well as the number of iterations k, rectifiable column vector x
cgls
- 用于解反问题的共轭梯度法，对于Ax=b，输入矩阵A，列向量b，以及迭代步数k，可求的列向量x-Solution of inverse problems for the conjugate gradient method, for Ax = b, the input matrix A, the column vector b, as well as the number of iterations k, rectifiable column vector x
mr2
- 用于解反问题的算法，对于Ax=b，输入矩阵A，列向量b，以及迭代步数k，可求的列向量x-The algorithm for solution of the inverse problem, for Ax = b, the input matrix A, the column vector b, as well as the number of iterations k, rectifiable column vector x
nu
- 用于解反问题的算法，对于Ax=b，输入矩阵A，列向量b，以及迭代步数k，可求的列向量x-The algorithm for solution of the inverse problem, for Ax = b, the input matrix A, the column vector b, as well as the number of iterations k, rectifiable column vector x
penta2
- Solves the problem Ax=b when A is pentadiagonal and strongly nonsingular. This is much faster than x=A\y for large matrices. -Solves the problem Ax=b when A is pentadiagonal and strongly nonsingular. This is much faster than x=A\y for lar
cramer
- Solve the system Ax=b.
lsq
- Least squares solution of Ax=b.
How-to-avoid-the-ax-reviewers
- 如何避免审稿人的大斧，十分经典，吐血提供，不看别后悔！-How to avoid the ax reviewers