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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প্রধান লেখক: Huber, Marco
বিন্যাস: Online
ভাষা:ইংরেজি
প্রকাশিত: KIT Scientific Publishing 2021
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অনলাইন ব্যবহার করুন:34619
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author Huber, Marco
author_browse Huber, Marco
author_facet Huber, Marco
author_sort Huber, Marco
collection Directory of Open Access Books
description 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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spelling doab-20.500.12854ir-547582023-12-20T18:40:45Z Nonlinear Gaussian Filtering : Theory, Algorithms, and Applications Huber, Marco QA75.5-76.95 Zustandsschätzung GaußprozesseBayesian statistics Kalman filter Gaussian processes Kalman-Filter state estimation filtering Bayes'sche Statistik bic Book Industry Communication::U Computing & information technology::UY Computer science 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. 2021-02-11T21:07:56Z 2021-02-11T21:07:56Z 2019-07-30 20:01:58 2015 book 34619 18636489 9783731503385 https://directory.doabooks.org/handle/20.500.12854/54758 eng Karlsruher Schriften zur Anthropomatik / Lehrstuhl für Interaktive Echtzeitsysteme, Karlsruher Institut für Technologie ; Fraunhofer-Inst. für Optronik, Systemtechnik und Bildauswertung IOSB Karlsruhe image/jpeg Attribution-ShareAlike 4.0 International https://www.ksp.kit.edu/9783731503385 KIT Scientific Publishing 10.5445/KSP/1000045491 10.5445/KSP/1000045491 68fffc18-8f7b-44fa-ac7e-0b7d7d979bd2 9783731503385 V, 270 p. open access
spellingShingle QA75.5-76.95
Zustandsschätzung
GaußprozesseBayesian statistics
Kalman filter
Gaussian processes
Kalman-Filter
state estimation
filtering
Bayes'sche Statistik
bic Book Industry Communication::U Computing & information technology::UY Computer science
Huber, Marco
Nonlinear Gaussian Filtering : Theory, Algorithms, and Applications
title Nonlinear Gaussian Filtering : Theory, Algorithms, and Applications
title_full Nonlinear Gaussian Filtering : Theory, Algorithms, and Applications
title_fullStr Nonlinear Gaussian Filtering : Theory, Algorithms, and Applications
title_full_unstemmed Nonlinear Gaussian Filtering : Theory, Algorithms, and Applications
title_short Nonlinear Gaussian Filtering : Theory, Algorithms, and Applications
title_sort nonlinear gaussian filtering theory algorithms and applications
topic QA75.5-76.95
Zustandsschätzung
GaußprozesseBayesian statistics
Kalman filter
Gaussian processes
Kalman-Filter
state estimation
filtering
Bayes'sche Statistik
bic Book Industry Communication::U Computing & information technology::UY Computer science
topic_facet QA75.5-76.95
Zustandsschätzung
GaußprozesseBayesian statistics
Kalman filter
Gaussian processes
Kalman-Filter
state estimation
filtering
Bayes'sche Statistik
bic Book Industry Communication::U Computing & information technology::UY Computer science
url 34619
work_keys_str_mv AT hubermarco nonlineargaussianfilteringtheoryalgorithmsandapplications