Nonlinear state and parameter estimation of spatially distributed systems (Karlsruhe Series on Intelligent Sensor-Actuator-Systems, Universität Karlsruhe) - Softcover
Synopsis
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.
"synopsis" may belong to another edition of this title.
Search results for Nonlinear state and parameter estimation of spatially...
Seller Image
Nonlinear state and parameter estimation of spatially distributed systems
Published by
KIT Scientific Publishing, 2009
ISBN 10: 3866443706
ISBN 13: 9783866443709
Used
8° Paperback
Seller: avelibro OHG, Dinkelscherben, Germany
Seller rating 5 out of 5 stars
8° Paperback. Condition: 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. Seller Inventory # 1834953
Seller Image
Nonlinear state and parameter estimation of spatially distributed systems
Published by
Karlsruher Institut Für Technologie Mai 2009, 2009
ISBN 10: 3866443706
ISBN 13: 9783866443709
New
Taschenbuch
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: 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. Seller Inventory # 9783866443709
Seller Image
Nonlinear state and parameter estimation of spatially distributed systems
Published by
KIT Scientific Publishing, 2009
ISBN 10: 3866443706
ISBN 13: 9783866443709
New
Kartoniert / Broschiert
Seller: moluna, Greven, Germany
Seller rating 5 out of 5 stars
Kartoniert / Broschiert. Condition: 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. Seller Inventory # 5587808
Buy New
£ 27.27
£ 41.98 shipping
Ships from Germany to U.S.A.
Ships from Germany to U.S.A.
Quantity: Over 20 available
Seller Image
Nonlinear state and parameter estimation of spatially distributed systems
Published by
Karlsruher Institut Für Technologie, Karlsruher Institut Für Technologie Okt 2014, 2014
ISBN 10: 3866443706
ISBN 13: 9783866443709
New
Taschenbuch
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: 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. Seller Inventory # 9783866443709
Seller Image
Nonlinear state and parameter estimation of spatially distributed systems
Published by
Karlsruher Institut Für Technologie, Karlsruher Institut Für Technologie, 2009
ISBN 10: 3866443706
ISBN 13: 9783866443709
New
Taschenbuch
Seller: AHA-BUCH GmbH, Einbeck, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: 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. Seller Inventory # 9783866443709
Seller Image
Nonlinear state and parameter estimation of spatially distributed systems
Published by
Karlsruher Institut für Technologie, 2014
ISBN 10: 3866443706
ISBN 13: 9783866443709
New
Taschenbuch
Seller: preigu, Osnabrück, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: 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. Seller Inventory # 105064186