  Optimal design of experiments for correlated processes is an increasingly
relevant and active research topic. Until now only heuristic methods were
available without a possibility to judge their quality. In this work we
complement the virtual noise approach by a convex formulation and an
equivalence theorem comparable to the uncorrelated case. Hence, it is now
possible to provide an upper performance bound against which alternative design
methods can be judged. We provide a comparison on some classical examples from
the literature.
