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Nonlinear state and parameter estimation of spatially distributed systems Felix Sawo
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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 | Böcker Pocketbok (Bok med mjukt omslag och limmad rygg) |
| Releasedatum | 16 oktober 2014 |
| ISBN13 | 9783866443709 |
| Utgivare | Karlsruher Institut für Technologie |
| Antal sidor | 176 |
| Mått | 148 × 210 × 10 mm · 264 g |
| Språk | Tyska |
