22 resultados para Discrete-Time Optimal Control
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The paper is a contribution to the theory of branching processes with discrete time and a general phase space in the sense of [2]. We characterize the class of regular, i.e. in a sense sufficiently random, branching processes (Φk) k∈Z by almost sure properties of their realizations without making any assumptions about stationarity or existence of moments. This enables us to classify the clans of (Φk) into the regular part and the completely non-regular part. It turns out that the completely non-regular branching processes are built up from single-line processes, whereas the regular ones are mixtures of left-tail trivial processes with a Poisson family structure.
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Representation of neural networks by dynamical systems is considered. The method of training of neural networks with the help of the theory of optimal control is offered.
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2000 Mathematics Subject Classification: 60J80.
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2000 Mathematics Subject Classification: 60J80.
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2000 Mathematics Subject Classification: 49L20, 60J60, 93E20
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Mathematics Subject Classification: 26A33, 45K05, 60J60, 60G50, 65N06, 80-99.
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The importance of “control variations” for obtaining local approximations of the reachable set of nonlinear control systems is well known. Heuristically, if one can construct control variations in all possible directions, then the considered control system is small-time locally controllable (STLC). Two concepts of control variations of higher order are introduced for the case of smooth control systems. The relation between these variations and the small-time local controllability is studied and a new sufficient STLC condition is proved.