1. A device for classifying in unsupervised training a pluralty of input vectors into classes comprising: (a) neural net having an input for receiving the input vectors and an output for providing a pattern of output activations associated with the input vector, and a memory for storing values of operational parameters of the net; (b) a stochastic labeling means, coupled to the output, for generating weighting factors for each of the classes upon mutually correlating the output activations of the patterns and for perfoming a stochastic selection using probabilities of a single class on the basis of probabilities weighted by the weighting factors; (c) an intensifying means coupled to the memory for intensifying differences between the patterns by modifying the values of the operational parameters upon re-supplying the test vectors in random order and for storing the modified values in the memory.