When 
is not positive definite, but symmetric, we can still
construct an orthogonal basis for the Krylov subspace
by three term recurrence relations.
Eliminating the
search directions
in equations (
)
and () gives a recurrence
which can be written in matrix form as
where 
is an 
tridiagonal matrix
In this case we have the problem that 
no
longer defines an inner product. However we can still try to minimize
the residual in the 
-norm by obtaining
that minimizes
Now we exploit the fact that if 
, then
is an orthonormal transformation with respect to
the current Krylov subspace:
and this final expression can simply be seen as a minimum norm least squares problem.
The element in the 
position of can be
annihilated by a simple Givens rotation and the resulting upper
bidiagonal system (the other subdiagonal elements having been removed
in previous iteration steps) can simply be solved, which leads to the
MINRES method (see Paige and Saunders [168]).
Another possibility is to solve the system
, as in the CG method (
is the upper
part of ). Other than in CG we cannot rely on
the existence of a Cholesky decomposition
(since is not positive
definite). An alternative is then to decompose by an
-decomposition. This again leads to simple recurrences and the
resulting method is known as SYMMLQ (see Paige and Saunders [168]).