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Nonlinear state and parameter estimation of spatially distributed systems
Felix Sawo
Nonlinear state and parameter estimation of spatially distributed systems
Felix Sawo
In this thesis two probabilistic model-based estimators are introduced that allow the reconstruction and identification of space-time continuous physical systems. The Sliced Gaussian Mixture Filter (SGMF) exploits linear substructures in mixed linear/nonlinear systems, and thus is well-suited for identifying various model parameters. The Covariance Bounds Filter (CBF) allows the efficient estimation of widely distributed systems in a decentralized fashion.
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Media | Książki Paperback Book (Książka z miękką okładką i klejonym grzbietem) |
Wydane | 16 października 2014 |
ISBN13 | 9783866443709 |
Wydawcy | Karlsruher Institut für Technologie |
Strony | 176 |
Wymiary | 148 × 210 × 10 mm · 217 g |
Język | English |
Zobacz wszystko od Felix Sawo ( np. Paperback Book )