Identification of dynamic object parameters

Adaptive algorithms for optimal identification of a restoration system are described, which permit correcting the coordinates of a linear dynamic system from a restricted set of observable coordinates in the presence of noise. The algorithms are based on the neural networkʹs method. The estimations obtained converge to the optimal ones in the sense of the minimum mean square deviation from the exact value.