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  2. Gauss–Seidel method - Wikipedia

    en.wikipedia.org/wiki/GaussSeidel_method

    In numerical linear algebra, the GaussSeidel method, also known as the Liebmann method or the method of successive displacement, is an iterative method used to solve a system of linear equations. It is named after the German mathematicians Carl Friedrich Gauss and Philipp Ludwig von Seidel .

  3. Conjugate gradient method - Wikipedia

    en.wikipedia.org/wiki/Conjugate_gradient_method

    The conjugate gradient method can also be used to solve unconstrained optimization problems such as energy minimization. It is commonly attributed to Magnus Hestenes and Eduard Stiefel , [ 1 ] [ 2 ] who programmed it on the Z4 , [ 3 ] and extensively researched it.

  4. List of numerical analysis topics - Wikipedia

    en.wikipedia.org/wiki/List_of_numerical_analysis...

    GaussSeidel method. Successive over-relaxation (SOR) — a technique to accelerate the GaussSeidel method Symmetric successive over-relaxation (SSOR) — variant of SOR for symmetric matrices; Backfitting algorithm — iterative procedure used to fit a generalized additive model, often equivalent to GaussSeidel; Modified Richardson ...

  5. Successive over-relaxation - Wikipedia

    en.wikipedia.org/wiki/Successive_over-relaxation

    To solve the equations, we choose a relaxation factor = and an initial guess vector = (,,,). According to the successive over-relaxation algorithm, the following table is obtained, representing an exemplary iteration with approximations, which ideally, but not necessarily, finds the exact solution, (3, −2, 2, 1) , in 38 steps.

  6. Relaxation (iterative method) - Wikipedia

    en.wikipedia.org/wiki/Relaxation_(iterative_method)

    Relaxation methods are used to solve the linear equations resulting from a discretization of the differential equation, for example by finite differences. [ 2 ] [ 3 ] [ 4 ] Iterative relaxation of solutions is commonly dubbed smoothing because with certain equations, such as Laplace's equation , it resembles repeated application of a local ...

  7. Iterative Stencil Loops - Wikipedia

    en.wikipedia.org/wiki/Iterative_Stencil_Loops

    Other notable examples include solving partial differential equations, [1] the Jacobi kernel, the GaussSeidel method, [2] image processing [1] and cellular automata. [3] The regular structure of the arrays sets stencil techniques apart from other modeling methods such as the Finite element method .

  8. Verlet integration - Wikipedia

    en.wikipedia.org/wiki/Verlet_integration

    When approximating the constraints locally to first order, this is the same as the GaussSeidel method. For small matrices it is known that LU decomposition is faster. Large systems can be divided into clusters (for example, each ragdoll = cluster). Inside clusters the LU method is used, between clusters the GaussSeidel method is used. The ...

  9. Multigrid method - Wikipedia

    en.wikipedia.org/wiki/Multigrid_method

    In other words, it can solve these problems to a given accuracy in a number of operations that is proportional to the number of unknowns. Assume that one has a differential equation which can be solved approximately (with a given accuracy) on a grid with a given grid point density .