Abstract
Exact finite-dimensional Bayesian filters exist only for a small class of systems. The previous chapter discussed the best known example, i.e., the Kalman Filter (KF) for linear systems subject to additive Gaussian uncertainties. Other examples are the filters of Beneš [25], which requires the measurement model to be linear, and Daum [61], applicable to a more general class of systems with nonlinear process and measurement models for which the posterior pdf is any exponential distribution.
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Lefebvre, T., Bruyninckx, H., De Schutter, J. 5 The Non-Minimal State Kalman Filter. In: Nonlinear Kalman Filtering for Force-Controlled Robot Tasks. Springer Tracts in Advanced Robotics, vol 19. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11533054_5
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DOI: https://doi.org/10.1007/11533054_5
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Publisher Name: Springer, Berlin, Heidelberg
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