Abstract
This paper presents recent results on conditionally Gaussian observed Markov switching models by incorporating fuzzy switches in the model, instead of hard ones. This kind of generalization is of interest for applications involving continuous switching regimes, such as tracking an object using cameras in intermittent sunlight and shadow conditions. The filter developed hereby is recursive, optimal, and exact, up to an approximation of integrals according to some fuzzy measures. Experiences on simulated and on real data-dealing with outdoor air temperature and power consumption of a building-confirm the accuracy and effectiveness of the proposed filter compared with the hard filter with “crisp” switches.
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