



![]() |
![[l_(11) 0 0; l_(21) l_(22) 0; l_(31) l_(32) l_(33)][u_(11) u_(12) u_(13); 0 u_(22) u_(23); 0 0 u_(33)]=[a_(11) a_(12) a_(13); a_(21) a_(22) a_(23); a_(31) a_(32) a_(33)]](http://mathworld.wolfram.com/images/equations/LUDecomposition/NumberedEquation2.gif)
![[l_(11)u_(11) l_(11)u_(12) l_(11)u_(13); l_(21)u_(11) l_(21)u_(12)+l_(22)u_(22) l_(21)u_(13)+l_(22)u_(23); l_(31)u_(11) l_(31)u_(12)+l_(32)u_(22) l_(31)u_(13)+l_(32)u_(23)+l_(33)u_(33)]=[a_(11) a_(12) a_(13); a_(21) a_(22) a_(23); a_(31) a_(32) a_(33)].](http://mathworld.wolfram.com/images/equations/LUDecomposition/NumberedEquation3.gif)
This gives three types of equations



This gives
equations for
unknowns (the decomposition is not unique), and can be solved using Crout's method. To solve the matrix equation



first solve
for
. This can be done by forward substitution


for
, ...,
. Then solve
for
. This can be done by back substitution




for
, ..., 1

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