Consistent classification of stochastic processes in the presence of dependent noise

The article is concerned with classification of stochastic processes in the presence of dependent noise whose distribution is unknown. A creterion is developed which distinguishes the hypotheses within finite time with specified probability of correct classification. The results are apilied to recognition of processes having fractional rational spectral densities.