Identification of Objects with Partially Unobservable Influences

Abstract

the methods of estimation of characteristics under conditions of uncertainty, systems of representation of incomplete observability of input signals are considered. Frequency transfer functions and spectral densities are used to identify the system. Methods of factor analysis and recurrent Kalman filter are used to restore unobservable effects and reduce the dimension of the object model.