The Jacobi method, also called the Jacobi iteration method, is an iterative algorithm from numerical linear algebra for finding the solution of a strictly diagonally dominant system of linear equations. Each diagonal element is solved for in turn using an approximate value for the others, and the process is repeated until the estimates converge. It is a stripped-down version of the Jacobi transformation method of matrix diagonalization, and it takes its name from the mathematician Carl Gustav Jacob Jacobi. Because each unknown is updated from the previous iterate only, the method is simple to state and is a standard first example of an iterative solver for linear systems.
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Source Jacobi method (Wikipedia)
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Source Wolfram MathWorld: Jacobi Method
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1. Wolfram MathWorld: Jacobi Method
Wolfram MathWorldMathWorld, article text (design technique)
The process is then iterated until it converges.
Uses Design Technique: Iterative Refinement, MathWorld, article text (technique relation)
The process is then iterated until it converges.
View the Source Jacobi method (Wikipedia)
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In numerical linear algebra, the Jacobi method (a.k.a. the Jacobi iteration method) is an iterative algorithm for determining the solutions of a strictly diagonally dominant system of linear equations.
In Field: Computational Science, Lead
In numerical linear algebra, the Jacobi method (a.k.a. the Jacobi iteration method) is an iterative algorithm for determining the solutions of a strictly diagonally dominant system of linear equations.
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