Abstract
In the classical pattern recognition problem, consideration is given to individual objects, each of which actually belongs to one of the finite number of classes and is presented for the recognition irrespective of other objects. Recognition objects often form a single interconnected array determined by the nature of the event involved, namely, its natural extent in time or in space along one or a few coordinates. As a consequence, the need arises to take consistent decisions about the classes for all elements of the array. The prior assumption consisting in the fact that neighboring objects more often belong to one class than to different classes will permit one to improve the recognition quality in comparison with the classical case of the independence of classes of separate objects.
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