Leonid Zhiteckii

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This paper deals with studying the asymptotical properties of multilayer neural networks models used for the adaptive identification of wide class of nonlinearly parameterized systems in stochastic environment. To adjust the neural network’s weights, the standard online gradient type learning algorithms are employed. The learning set is assumed to be(More)
The steady-state control of multivariable nonlinear discrete-time, time-invariant systems in the presence of arbitrary unmeasurable but bounded disturbances is addressed in this paper. The pseudoinverse model approach as a unified concept to cope with possible noninvertibility and to achieve a desired behavior of a wide class of both linear and of nonlinear(More)
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