Nonlinear Gaussian Filtering : Theory, Algorithms, and Applications
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 f...
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| Format: | eBook |
| Language: | English |
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KIT Scientific Publishing
2015
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| Series: | Karlsruher Schriften zur Anthropomatik / Lehrstuhl für Interaktive Echtzeitsysteme, Karlsruher Institut für Technologie ; Fraunhofer-Inst. für Optronik, Systemtechnik und Bildauswertung IOSB Karlsruhe
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| Collection: | Directory of Open Access Books - Collection details see MPG.ReNa |
| 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. |
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| Item Description: | Creative Commons (cc), https://creativecommons.org/licenses/by-sa/4.0/ |
| Physical Description: | 1 electronic resource (V, 270 p. p.) |
| ISBN: | 9783731503385 1000045491 |