Nonlinear Gaussian Filtering: Theory, Algorithms and Applications - Couverture souple

Huber, Marco

 
9783731503385: Nonlinear Gaussian Filtering: Theory, Algorithms and Applications

Synopsis

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.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Présentation de l'éditeur

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.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Autres éditions populaires du même titre

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

Edition présentée

ISBN 10 :  1013280687 ISBN 13 :  9781013280689
Editeur : Saint Philip Street Press, 2020
Couverture souple