Title :
Finite fast fourier transform filter for discrete linear systems with Markov jump parameters
Author :
Allam, Sebastien ; Dufour, Francois ; Bertrand, Pierre
Author_Institution :
Lab. des signaux et Syst., Supelec, Gif-sur-Yvette, France
fDate :
Aug. 31 1999-Sept. 3 1999
Abstract :
Linear discrete time stochastic dynamical systems with switching parameters may represent a wide class of physical processes. Given the fact that, for non linear systems, the conditional density has no finite parametrization, optimal filters for this class of models are generally infinite dimensional. An exact recursive hybrid filter form has been recently found by Elliott and al [3]. The purpose of this note is to present a new simple approximation scheme of this exact version, which avoids the exponential growth memory problem of the original form. This new numerical scheme is shown to be computationnally efficient. Its implementation is discussed and a comparison of its performances with the Interacting Multiple Models (IMM) algorithm [2] shows its efficiency.
Keywords :
approximation theory; discrete systems; fast Fourier transforms; linear systems; stochastic systems; Markov jump parameters; exact recursive hybrid filter form; exponential growth memory problem; finite fast Fourier transform filter; interacting multiple model algorithm; linear discrete time stochastic dynamical systems; optimal filters; simple approximation scheme; switching parameters; Computational modeling; Fourier transforms; Interpolation; Markov processes; Mathematical model; Noise; Switching parameter system estimation; density reconstruction; filtering and tracking algorithm;
Conference_Titel :
Control Conference (ECC), 1999 European
Conference_Location :
Karlsruhe
Print_ISBN :
978-3-9524173-5-5