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In applied mathematics, '''symmetric successive overrelaxation (SSOR)''',<ref>[http://www.cfd-online.com/Wiki/Iterative_methods Iterative methods] at CFD-Online wiki</ref> is a [[preconditioner]]. | |||
If the original matrix can be decomposed into diagonal, lower and upper tridiagonal as <math>A=D+L+L^T</math> then SSOR preconditioner matrix is defined as | |||
: <math>M=(D+L) D^{-1} (D+L)^T</math> | |||
It can also be parametrised by <math>\omega</math> as follows.<ref>[http://www.netlib.org/linalg/html_templates/node58.html SSOR preconditioning] at [[Netlib]]</ref> | |||
:<math>M(\omega)={1\over{2-\omega}} \left ( {1\over\omega} D + L \right ) \left ( {1\over\omega} D \right)^{-1} \left ( {1\over\omega D} + L\right)</math> | |||
== See also== | |||
*[[Successive over-relaxation]] | |||
== References == | |||
<references/> | |||
[[Category:Numerical linear algebra]] | |||
{{mathapplied-stub}} | |||
Latest revision as of 19:18, 24 January 2014
In applied mathematics, symmetric successive overrelaxation (SSOR),[1] is a preconditioner.
If the original matrix can be decomposed into diagonal, lower and upper tridiagonal as then SSOR preconditioner matrix is defined as
It can also be parametrised by as follows.[2]
See also
References
- ↑ Iterative methods at CFD-Online wiki
- ↑ SSOR preconditioning at Netlib