Felix sawo (6 risultati)

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    • Lingua: Inglese

      Editore: KIT Scientific Publishing, 2009

      3866443706 / 9783866443709

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      Da: avelibro OHG, Dinkelscherben, Germaniaavelibro OHG

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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.

    • Lingua: Inglese

      Editore: Karlsruher Institut Für Technologie, Karlsruher Institut Für Technologie, 2009

      3866443706 / 9783866443709

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      Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

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      Condizione: Nuovo

      EUR 30,90

      EUR 61,32 spedizione 
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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.

    • Lingua: Inglese

      Editore: Karlsruher Institut Für Technologie Mai 2009, 2009

      3866443706 / 9783866443709

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      Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.

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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.

    • Lingua: Inglese

      Editore: KIT Scientific Publishing, 2009

      3866443706 / 9783866443709

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      Da: moluna, Greven, Germaniamoluna

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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.

    • Lingua: Inglese

      Editore: Karlsruher Institut Für Technologie, Karlsruher Institut Für Technologie Okt 2014, 2014

      3866443706 / 9783866443709

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      Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000

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      Condizione: Nuovo

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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.

    • Lingua: Inglese

      Editore: Karlsruher Institut für Technologie, 2014

      3866443706 / 9783866443709

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      Da: preigu, Osnabrück, Germaniapreigu

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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.