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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Taschenbuch. Zustand: 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. Artikel-Nr. 9783731503385
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Taschenbuch. Zustand: 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. Artikel-Nr. 104810334
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Paperback. Zustand: Brand New. 304 pages. 8.27x5.83x0.72 inches. In Stock. Artikel-Nr. 3731503387
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