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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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Nonlinear state and parameter estimation of spatially distributed systems
Editore:
KIT Scientific Publishing, 2009
ISBN 10: 3866443706
ISBN 13: 9783866443709
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8° Paperback. Condizione: Sehr gut. 153 S. 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. B05-04-03C Sprache: Englisch Gewicht in Gramm: 300. Codice articolo 1834953
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Nonlinear state and parameter estimation of spatially distributed systems
Editore:
Karlsruher Institut Für Technologie Mai 2009, 2009
ISBN 10: 3866443706
ISBN 13: 9783866443709
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 176 pp. Englisch. Codice articolo 9783866443709
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Nonlinear state and parameter estimation of spatially distributed systems
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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/nonlin. Codice articolo 5587808
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Nonlinear state and parameter estimation of spatially distributed systems
ISBN 10: 3866443706
ISBN 13: 9783866443709
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Books on Demand GmbH, Überseering 33, 22297 Hamburg 176 pp. Englisch. Codice articolo 9783866443709
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Nonlinear state and parameter estimation of spatially distributed systems
ISBN 10: 3866443706
ISBN 13: 9783866443709
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Codice articolo 9783866443709
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Nonlinear state and parameter estimation of spatially distributed systems
Editore:
Karlsruher Institut für Technologie, 2014
ISBN 10: 3866443706
ISBN 13: 9783866443709
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Da: preigu, Osnabrück, Germania
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Taschenbuch. Condizione: Neu. Nonlinear state and parameter estimation of spatially distributed systems | Felix Sawo | Taschenbuch | 176 S. | Englisch | 2014 | Karlsruher Institut für Technologie | EAN 9783866443709 | Verantwortliche Person für die EU: Karlsruher Institut für Technologie (KIT), Institut AIFB, Kaiserstr. 89, 76133 Karlsruhe, verlag[at]aifb[dot]uni-karlsruhe[dot]de | Anbieter: preigu Print on Demand. Codice articolo 105064186
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