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Nonlinear Gaussian Filtering : Theory, Algorithms, and Applications / by Marco Huber

By: Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Karlsruher Schriften zur Anthropomatik ; 19Publisher: Karlsruhe : KIT Scientific Publishing, 2015Description: Online-RessourceISBN:
  • 9783731503385
Other title:
  • Nonlinear-Gaussian-Filtering
Subject(s): Genre/Form: Additional physical formats: Erscheint auch als: Nonlinear Gaussian Filtering. Druck-Ausgabe Karlsruhe : KIT Scientific Publishing, 2015. XII, 270 S.DDC classification:
  • 510
  • 004
  • 004
RVK: RVK: ST 134Local classification: Lokale Notation: inf 11DOI: DOI: 10.5445/KSP/1000045491 | 10.5445/KSP/1000044922Online resources: Notes: Anmerkungen: Elektronische RessourceNote: Hinweis: Elektronische RessourceDissertation note: Zugl.: Karlsruhe, KIT, Habil.-Schrift, 2014 Summary: 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.PPN: PPN: 820849766Package identifier: Produktsigel: H-ZDB-104-KIT
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