Nonlinear Gaussian Filtering: Theory, Algorithms and Applications - Brossura

Huber, Marco

 
9783731503385: Nonlinear Gaussian Filtering: Theory, Algorithms and Applications

Sinossi

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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9781013280689: Nonlinear Gaussian Filtering: Theory, Algorithms, and Applications

Edizione in evidenza

ISBN 10:  1013280687 ISBN 13:  9781013280689
Casa editrice: Saint Philip Street Press, 2020
Brossura