The present paper explores the dynamic level of information sensory fusion which is to be appropriate for hardware implementations. We associate to multitracking sensors their abstractions, being discrete time multihead state circuits. We presume sensors are to be independent from each other and there are no direct interfaces between them. The fusion is achieved by sensor-to-sensor track association which is controlled by the global state transition system. We investigate synchronous and asynchronous fusion models over common and distributed resource spaces and we compare the recognition capacities of these and some other models, like Turing Machines, stack automata etc.. Then the fusioned circuits are applied to analyze arithmetical predicates, social games and an unsolved "Syracuse Conjecture".
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