Title :
Identification of a noisy stochastic heat equation with the EM algorithm
Author_Institution :
Sch. of Electr. Eng., New South Wales Univ., Sydney, NSW, Australia
Abstract :
Despite the considerable literature on ill-conditioned inverse problem of estimation of spatially varying parameters in partial differential equations an important case has gone untreated. This is when there is noise in both the partial differential equation and the observations. Previous spatially varying parameter estimation work allows one or the other but not both. We show how to deal with this case by developing a penalised EM (expectation-maximization) algorithm for noisy observations of the stochastic heat equation.
Keywords :
inverse problems; maximum likelihood estimation; optimisation; partial differential equations; stochastic processes; expectation maximization algorithm; identification; inverse problem; maximum likelihood estimation; noisy stochastic heat equation; partial differential equations; spatially varying parameters estimation; Australia; Differential equations; Integral equations; Inverse problems; Parameter estimation; Partial differential equations; State estimation; Stochastic processes; Stochastic resonance; White noise;
Conference_Titel :
Decision and Control, 2002, Proceedings of the 41st IEEE Conference on
Print_ISBN :
0-7803-7516-5
DOI :
10.1109/CDC.2002.1185083