Preconditioning reduces the condition number of the
coefficient matrix of a linear system to accelerate the convergence
when the system is solved by an iterative method.
This constructs a new instance of
for a coefficient matrix.
This identity preconditioner is used when no preconditioning is applied.
The Jacobi (or diagonal) preconditioner is one of the simplest forms of
preconditioning, such that the preconditioner is the diagonal of
the coefficient matrix, i.e.,
P = diag(A).
SSOR preconditioner is derived from a symmetric coefficient matrix
which is decomposed as
A = D + L + L
The SSOR preconditioning matrix is defined as
M = (D + L)D
or, parameterized by -1(D + L) t
M(ω) = (1/(2 - ω))(D / ω + L)(D / ω) -1(D / ω + L) t