  Asymptotic behavior of the singular value decomposition (SVD) of blown up
matrices and normalized blown up contingency tables exposed to Wigner-noise is
investigated.It is proved that such an m\times n matrix almost surely has a
constant number of large singular values (of order \sqrt{mn}), while the rest
of the singular values are of order \sqrt{m+n} as m,n\to\infty. Concentration
results of Alon et al. for the eigenvalues of large symmetric random matrices
are adapted to the rectangular case, and on this basis, almost sure results for
the singular values as well as for the corresponding isotropic subspaces are
proved. An algorithm, applicable to two-way classification of microarrays, is
also given that finds the underlying block structure.
