State smoothing and filtering using a constant memory for dynamic systems with nonlinear interference and missing observations.

Abstract

Time-varying finite state models and interpolating functions are used to estimate the states of nonlinear discrete dynamic models with nonlinear interference and missing observations. State estimation is carried out in blocks so that its implementation requires a constant memory.