Simultaneity in the problems of classification of finite objects

Consideration is given to the problem of efficient computability of solvable models of finite objects classification. We investigate the constructivization of simultaneity (extremely short cycle) conditions of decision adoption in the classification. Simultaneity is achieved by parallel comparing of the components of the unknown implementation with informative elements of all etalons in the training sample. Constructivization of simultaneity conditions includes: a selection of informative elements (identification labels) in the informative areas of classified sets; the parallel component-wise comparison of the unknown realization of a finite object with informative elements of etalons from the training set. The obtained results of simultaneous decision trees in classification is interpreted in neural networks, in a generalized model of recognition, in problems of identification.