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Particle filters have become very popular signal processing tools for problems that involve nonlinear tracking of an unobserved signal of interest given a series of related observations. In this paper we propose a new scheme for particle filtering when the observed data are possibly contaminated with outliers. An outlier is an observation that has been generated by some (unknown) mechanism different...
One of the most basic problems in science and engineering is the assessment of a considered model. The model should describe a set of observed data and the objective is to find ways of deciding if the model should be rejected. It seems that this is an ill-conditioned problem because we have to test the model against all the possible alternative models. In this paper we use the Kolmogorov-Smirnov statistic...
In this paper we address the problem of applying particle filtering to complex systems. In general, we consider complex systems as ones with nonlinearities and high dimensionality of the state space. We examine strategies for filtering where the state space is partitioned into subspaces and where each subspace is explored by its own particle filter. These particle filters are interconnected and communicate...
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