Incomplete Cholesky factorization
From CFD-Wiki
Cholesky Factorization
When the square matrix A is symmetric and positive definite then it has an efficient triangular decomposition. Symmetric means that aij = aji for i,j = 1, ... , N. While positive definite means that
In cholesky factorization we construct a lower triangular matrix L whose transpose LT can itself serve as upper triangular part.
In other words we have
L LT = A
Algorithm for full matrix A
We have by definition
From this we can easily obtain
for := 1 step 1 until N do
and
; where j = i+1, i+2, ..., N
end (i-loop)
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