  In this paper, we present a class of high order methods to approximate the
singular value decomposition of a given complex matrix (SVD). To the best of
our knowledge, only methods up to order three appear in the the literature. A
first part is dedicated to defline and analyse this class of method in the
regular case, i.e., when the singular values are pairwise distinct. The
construction is based on a perturbation analysis of a suitable system of
associated to the SVD (SVD system). More precisely, for an integer $p$ be
given, we define a sequence which converges with an order $p + 1$ towards the
left-right singular vectors and the singular values if the initial
approximation of the SVD system satisfies a condition which depends on three
quantities : the norm of initial approximation of the SVD system, the greatest
singular value and the greatest inverse of the modulus of the difference
between the singular values. From a numerical computational point of view, this
furnishes a very efficient simple test to prove and certifiy the existence of a
SVD in neighborhood of the initial approximation. We generalize these result in
the case of clusters of singular values. We show also how to use the result of
regular case to detect the clusters of singular values and to define a notion
of deflation of the SVD. Moreover numerical experiments confirm the theoretical
results.
