Preconditioned conjugate gradient method: Difference between revisions

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#REDIRECT [[Conjugate gradient method#The preconditioned conjugate gradient method]]
The [[conjugate gradient method]] is a [[numerical analysis|numerical algorithm]] that solves a [[system of linear equations]]
{{R to section}}
 
:<math>A x= b.\,</math>
 
If the [[matrix]] 'A' is [[ill-conditioned]], i.e. it has a large [[condition number]] <math>\kappa(A)</math>, it is often useful to use a [[preconditioner|preconditioning matrix]] <math>P^{-1}</math> that is chosen such that <math>P^{-1} \approx A^{-1}</math> and solve the system
 
:<math> P^{-1}Ax = P^{-1}b,\,</math>
 
instead.
 
==External links==
* [http://www.math-linux.com/spip.php?article55 Preconditioned Conjugate Gradient] – math-linux.com
[[Category:Numerical linear algebra]]
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