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In linear systems, the two main classes of relaxation methods are stationary iterative methods, and the more general Krylov subspace methods. The Jacobi method is a simple relaxation method. The Gauss–Seidel method is an improvement upon the Jacobi method.
algorithm Gauss–Seidel method is inputs: A, b output: φ Choose an initial guess φ to the solution repeat until convergence for i from 1 until n do σ ← 0 for j from 1 until n do if j ≠ i then σ ← σ + a ij φ j end if end (j-loop) φ i ← (b i − σ) / a ii end (i-loop) check if convergence is reached end (repeat)
In numerical linear algebra, the method of successive over-relaxation (SOR) is a variant of the Gauss–Seidel method for solving a linear system of equations, resulting in faster convergence. A similar method can be used for any slowly converging iterative process .
Gauss–Seidel method. Successive over-relaxation (SOR) — a technique to accelerate the Gauss–Seidel 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 Gauss–Seidel; Modified Richardson ...
Gauss–Seidel method; J. Jacobi method; M. ... Successive over-relaxation This page was last edited on 18 May 2011, at 22:20 (UTC). Text is available under the ...
Iterative Stencil Loops (ISLs) or Stencil computations are a class of numerical data processing solution [1] which update array elements according to some fixed pattern, called a stencil. [2] They are most commonly found in computer simulations , e.g. for computational fluid dynamics in the context of scientific and engineering applications.
The main idea of multigrid is to accelerate the convergence of a basic iterative method (known as relaxation, which generally reduces short-wavelength error) by a global correction of the fine grid solution approximation from time to time, accomplished by solving a coarse problem. The coarse problem, while cheaper to solve, is similar to the ...
A relaxation is an approximation of a difficult problem by a nearby problem that is easier to solve. A solution of the relaxed problem provides information about the original problem. For example, a linear programming relaxation of an integer programming problem