In linear algebra
means the following: we start with vectors v1
in an inner product space
, most commonly the Euclidean space Rn
which are linearly independent
and we want to find mutually orthogonal
which generate the same subspace
as the vectors v1
One method for performing orthogonalization is the Gram-Schmidt process.
When performing orthogonalization on a computer, the Householder transformation is usually preferred over the Gram-Schmidt process since it is more numerically stable, i.e. rounding errors tend to have less serious effects.