Prognostication of dynamic processes by means of time series models with multirate discretization

Abstract

Theoretical propositions concerning multirate system design for prognostication of dynamic coordinates of one- and multidimensional processes under discretization of input disturbances with small periods of sampling and output coordinates with large periods of sampling are considered. Dynamics of stationary processes is represented by autoregression and sliding mean models and those of nonstationary ones by autoregression and integrated sliding mean models with multirate discretization.