@conference {Evans1997Finite-dimensio,
title = {Finite dimensional filters for random parameter AR models},
booktitle = {American Control Conference, 1997. Proceedings of the 1997},
volume = {5},
year = {1997},
month = {jun.},
pages = {2836 -2840 vol.5},
abstract = {In this paper exact finite dimensional filters are derived for a class of doubly stochastic autoregressive models. The parameters of the doubly stochastic autoregressive process vary according to a nonlinear function of a Gauss-Markov process. We develop a difference equation for the evolution of an unnormalized conditional density related to the state of the doubly stochastic autoregressive process. We then give a characterization of the general solution followed by examples for which the state of the filter is determined by a finite number of sufficient statistics. These new finite dimensional filters are built upon the discrete-time Kalman filter},
keywords = {autoregressive models, autoregressive processes, difference equation, difference equations, discrete-time Kalman filter, filtering theory, finite dimensional filters, Gauss-Markov process, Kalman filters, probability, stochastic AR models, stochastic processes, unnormalized conditional density},
doi = {10.1109/ACC.1997.611973},
url = {http://dx.doi.org/10.1109/ACC.1997.611973},
author = {Evans, J. and Krishnamurthy, V.}
}