  In comparing the behavior of an energy spectrum to the predictions of random
matrix theory one must transform the spectrum such that the averaged level
spacing is constant, a procedure known as unfolding. Once energy spectrums
belong to an ensemble where there are large realization-to-realization
fluctuations the canonical methods for unfolding fail. Here we show that
singular value decomposition can be used even for the challenging situations
where the ensemble is composed out of realizations originating from a different
range of parameters resulting in a non-monotonous local density of states. This
can be useful in experimental situations for which the physical parameters can
not be tightly controlled, of for situations for which the local density of
states is strongly fluctuating.

Disordered Systems and Neural Networks;Quantum Physics