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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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| Medios de comunicación | Libros Paperback Book (Libro con tapa blanda y lomo encolado) |
| Publicado | 16 de octubre de 2014 |
| ISBN13 | 9783866443709 |
| Editores | Karlsruher Institut für Technologie |
| Páginas | 176 |
| Dimensiones | 148 × 210 × 10 mm · 217 g |
| Lengua | Inglés |
