Regularization of problem of processing measurement data under conditions of a priori uncertainty

Using regularization procedures, the problem of identification of the parameters of nonlinear objects with minimal a priori information on the probabilistic characteristics of the measurement noise and disturbandes is solved on the basis of the conception of the inverse problems of dynamics. The algorithm which is obtained remains stable in the presence of errors in the input data and is oriented towards the contemporary capabilities of computer engineering. Results of a numerical experiment are presented.