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Record Nr. |
UNINA9910346924403321 |
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Autore |
Sawo Felix |
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Titolo |
Nonlinear state and parameter estimation of spatially distributed systems |
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Pubbl/distr/stampa |
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KIT Scientific Publishing, 2009 |
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ISBN |
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Descrizione fisica |
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1 online resource (XI, 153 p. p.) |
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Collana |
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Karlsruhe Series on Intelligent Sensor-Actuator-Systems, Universität Karlsruhe / Intelligent Sensor-Actuator-Systems Laboratory |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Sommario/riassunto |
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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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