Nonlinear Gaussian Filtering: Theory, Algorithms and Applications - Tapa blanda

Huber, Marco

 
9783731503385: Nonlinear Gaussian Filtering: Theory, Algorithms and Applications
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ISBN 10: 3731503387 ISBN 13: 9783731503385
Editorial: KIT Scientific Publishing, 2015

Sinopsis

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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Reseña del editor

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.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
KIT Scientific Publishing
Año de publicación
2015
Idioma
Inglés
ISBN 10 
3731503387
ISBN 13 
9783731503385
Encuadernación
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Número de páginas
304
Contacto del fabricante
no disponible
Persona responsable
no disponible

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

Edición Destacada

ISBN 10:  1013280687 ISBN 13:  9781013280689
Editorial: Saint Philip Street Press, 2020
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