Title 
Summary 
Primary Author 
Date 

This is a collection of routines comparing different iterative schemes
for approximating the solution of a system of linear equations. 
Bernd Flemisch 
20020808 

Conjugate Gradients method for solving a system of linear equations Ax = f . The matrix A must be symmetric and positive definite. 
Andreas Klimke 
20030513 

This GUI demonstrates the iterative methods to find eigenvalues of a given matrix, using power method, inverse power method and QRIteration. 
M2TUM 
20040113 

Function Gauss_Seidel(A, b, N) iteratively solves a system of linear equations whereby A is the coefficient matrix, b the righthand side column vector and N the maximum number of iterations. A transition/iteration matrix approach is implemented, with Tg 
Alain kapitho 
20070814 

resolvs a liniar sistem using iterativ method 
Ionescu Alin 
20070515 

GUI application for solving a system of equations using the Gradient and the Conjugate Gradients method. 
M2TUM 
20030523 

This is a simple function to track the subspace of a signal 
Gurudatha Pai 
20090115 

multiple versions of the incomplete LUfactorization 
M2TUM 
20090730 

An interactive environment for iterative solvers. 
Timo Betcke 
20030519 

Function Jacobi(A, b, N) iteratively solves a system of linear equations whereby A is the coefficient matrix, b the righthand side column vector and N the maximum number of iterations. As with the Gauss_Seidel(A, b, N) function, a transition matrix appro 
Alain kapitho 
20070814 

Function that allows to solve linear systems by the Jacobi's iterative method. 
Alexeis Companioni 
20080504 

Multigrid solver for scalar linear elliptic PDEs. Beat the direct solver! 
Bernd Flemisch 
20040329 

solves the systems of linear equations
(A'*A+TAU(I)*EYE(N))*X(:,I)=A'*B (I=1:L)
for X with the multishift CGLS algorithm.
The matlab code is written by Gerard Sleijpen and Jasper van den Eshof. 
Jasper van den Eshof 
20040521 

This project simulate numerically the process of solution of orange droplet in a soup. Program is written in Matlab environment and uses a userfriendly interface to show the solution process versus time.

Ahmad Kolahi 
20050731 

Preconditioned conjugate gradients with extremal eigenvalue estimates 
Talal Rahman 
20020416 

Implementation of the preconditioned gradients method, including examples for Jacobi & GaussSeidel preconditioners. 
Andreas Klimke 
20030513 

Function that allows to solve linear systems by the Seidel's iterative method. 
Alexeis Companioni 
20080504 

Comparison regarding convergence rate of the Jacobi, GaussSeidel, and optimum SOR iterative linear equation system solvers for the laplace equation. 
Andreas Klimke 
20020506 

Function SOR(A,b,N) solves iteratively the linear system Ax = b, N being the maximum number of iterations. Iterations are implemented in matrix form as x(k+1) = Tw*x(k) + c, with Tw being the transition/iteration matrix and c a constant vector. the optim 
Alain kapitho 
20070814 