A novel strategy (which we call" minimum model error'* estimation) for postexperiment
optimal state estimation of discretely measured dynamic systems is developed and …

A technique is presented for processing noisy state-observable time domain measurements
of a nonlinear dynamic system in order to optimally estimate both the state vector trajectory …

The paper gives an overview of various methods for identifying dynamic errors-in-variables
systems. Several approaches are classified by how the original information in time-series …

Sequential estimators are derived for suboptimal adaptive estimation of the unknown a priori
state and observation noise statistics simultaneously with the system state. First-and second …

A system identi cation method to extract the disturbance-free dynamics and the disturbance
effect correctly despite the presence of unknown periodic disturbances is presented. The …

The problem of assessing the quality of a given, or estimated, model is a central issue in
system identification. Various new techniques for estimating bias and variance contributions …

The problem of identifying parameters in a dynamic model is considered based on the
premise that certain parameters not being estimated are not known precisely. A procedure is …

A real-time predictive lter is derived for nonlinear systems. The major advantage of this new
lter over conventional lters is that it provides a method of determining optimal state estimates …

This article deals with state estimation of nonlinear stochastic dynamic systems. The stress is
laid on general introduction of the selected estimation methods, description of their …

The basic ideas behind the parameter estimation methods are discussed in a general
setting. The application to estimation or parameters in dynamical systems is treated in detail …