Articles liés à Nonlinear Gaussian Filtering: Theory, Algorithms and...

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.

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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.

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