Neural networks for identification of nonlinear systems under random piecewise polynomial disturbances

The problem of identification of a nonlinear dynamic system is considered. ii two-layer neural network is used for the solution of the problem. System s disturbed with unmeasurable noise are considered, although it is known th at the disturbance is a random piecewise polynomial process. Absorption pol ynomials and nonquadratic loss functions are used to reduce the effect of t his disturbance on the estimates of the optimal memory of the neural-networ k model.