Fixed-lag smoother for reduced state space modelCP11

Time-variant inverse problems are naturally cast as state space problems. In state estimation, using a smoother as the estimator results in a smaller estimation errors than a Kalman-type filter. However, this induces an augmented high-dimensional problem. To deal with this challenge, we construct a reduced state space model incorporating approximation errors. We derive the corresponding fixed-lag smoother and apply to an imaging problem induced by a stochastic advection-diffusion equation with unknown temporal boundary conditions.

This presentation is part of Contributed Presentation “CP11 - Contributed session 11

Pascal Eun Sig Cheon (University of Auckland)
bayesian methods, computed tomography, image reconstruction, inverse problems, numerical linear algebra, partial differential equation models, statistical inverse estimation methods, stochastic processes