Synopsis
By restricting to Gaussian distributions, the optimal Bayesian filtering problem can be transformed into an algebraically simple form, which allows for computationally efficient algorithms. Three problem settings are discussed in this thesis: (1) filtering with Gaussians only, (2) Gaussian mixture filtering for strong nonlinearities, (3) Gaussian process filtering for purely data-driven scenarios. For each setting, efficient algorithms are derived and applied to real-world problems.
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Nonlinear Gaussian Filtering : Theory, Algorithms, and Applications
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Karlsruher Institut Für Technologie Mrz 2015, 2015
ISBN 10: 3731503387
ISBN 13: 9783731503385
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -By restricting to Gaussian distributions, the optimal Bayesian filtering problem can be transformed into an algebraically simple form, which allows for computationally efficient algorithms. Three problem settings are discussed in this thesis: (1) filtering with Gaussians only, (2) Gaussian mixture filtering for strong nonlinearities, (3) Gaussian process filtering for purely data-driven scenarios. For each setting, efficient algorithms are derived and applied to real-world problems. 304 pp. Englisch. Seller Inventory # 9783731503385
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Nonlinear Gaussian Filtering : Theory, Algorithms, and Applications
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KIT Scientific Publishing, 2015
ISBN 10: 3731503387
ISBN 13: 9783731503385
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. By restricting to Gaussian distributions, the optimal Bayesian filtering problem can be transformed into an algebraically simple form, which allows for computationally efficient algorithms. Three problem settings are discussed in this thesis: (1) filtering . Seller Inventory # 18985056
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Nonlinear Gaussian Filtering : Theory, Algorithms, and Applications
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Karlsruher Institut Für Technologie, Karlsruher Institut Für Technologie Mär 2015, 2015
ISBN 10: 3731503387
ISBN 13: 9783731503385
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -By restricting to Gaussian distributions, the optimal Bayesian filtering problem can be transformed into an algebraically simple form, which allows for computationally efficient algorithms. Three problem settings are discussed in this thesis: (1) filtering with Gaussians only, (2) Gaussian mixture filtering for strong nonlinearities, (3) Gaussian process filtering for purely data-driven scenarios. For each setting, efficient algorithms are derived and applied to real-world problems.Books on Demand GmbH, Überseering 33, 22297 Hamburg 304 pp. Englisch. Seller Inventory # 9783731503385
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Nonlinear Gaussian Filtering : Theory, Algorithms, and Applications
Published by
Karlsruher Institut Für Technologie, 2015
ISBN 10: 3731503387
ISBN 13: 9783731503385
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - By restricting to Gaussian distributions, the optimal Bayesian filtering problem can be transformed into an algebraically simple form, which allows for computationally efficient algorithms. Three problem settings are discussed in this thesis: (1) filtering with Gaussians only, (2) Gaussian mixture filtering for strong nonlinearities, (3) Gaussian process filtering for purely data-driven scenarios. For each setting, efficient algorithms are derived and applied to real-world problems. Seller Inventory # 9783731503385
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Nonlinear Gaussian Filtering : Theory, Algorithms, and Applications
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Karlsruher Institut für Technologie, 2015
ISBN 10: 3731503387
ISBN 13: 9783731503385
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Taschenbuch. Condition: Neu. Nonlinear Gaussian Filtering : Theory, Algorithms, and Applications | Marco Huber | Taschenbuch | 304 S. | Englisch | 2015 | Karlsruher Institut für Technologie | EAN 9783731503385 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Seller Inventory # 104810334
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Nonlinear Gaussian Filtering: Theory, Algorithms and Applications
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KIT Scientific Publishing, 2015
ISBN 10: 3731503387
ISBN 13: 9783731503385
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Paperback. Condition: Brand New. 304 pages. 8.27x5.83x0.72 inches. In Stock. Seller Inventory # 3731503387
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