Robust Filtering

Robust Recursive Kalman–Filtering

We consider robust recursive filtering in the case of a linear, finite-dimensional and timediscrete state-space model with Euclidean state space. Insisting on recursivity for computational reasons, we come up with a new procedure, the rLS-filter, using a Huberized correction-step in the Kalman-filter recursions. Simulation results for ideal and contaminated data indicate that this procedure ach...

Robust Guided Image Filtering

The process of using one image to guide the filtering process of another one is called Guided Image Filtering (GIF). The main challenge of GIF is the structure inconsistency between the guidance image and the target image. Besides, noise in the target image is also a challenging issue especially when it is heavy. In this paper, we propose a general framework for Robust Guided Image Filtering (R...

Robust Nonlinear 3fm Filtering

This paper investigates the robust nonlinear Hfiltering problem for nonlinear systems with uncertainties which are described by integral functional constraints. The objective is to design a dynamic filter such that the &-gain from an exogenous input to an estimation error is minimized or guaranteed to be less or equal to a prescribed value for all admissable uncertainties. We establish the inte...

H2 Optimal Robust Filtering

Nonlinear Filtering and Robust Learning

We refine and apply particle filtering algorithms that emphasize portions of the filtered distribution most pertinent to a decision maker. We illustrate our algorithms in an equilibrium model with investors who design robust decision rules by exponentially tilting probabilities of a baseline statistical model.