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On the relation between Gaussian process quadratures and sigma-point methods

A. S. Arkkä ; J. Hartikainen ; Lennart Svensson (Institutionen för signaler och system, Signalbehandling) ; Fredrik Sandblom
Journal of Advances in Information Fusion (1557-6418). Vol. 11 (2016), 1, p. 31-46.
[Artikel, refereegranskad vetenskaplig]

This article is concerned with Gaussian process quadratures, which are numerical integration methods based on Gaussian process regression methods, and sigma-point methods, which are used in advanced non-linear Kalman filtering and smoothing algorithms. We show that many sigma-point methods can be interpreted as Gaussian process quadrature based methods with suitably selected covariance functions. We show that this interpretation also extends to more general multivariate Gauss-Hermite integration methods and related spherical cubature rules. Additionally, we discuss different criteria for selecting the sigma-point locations: exactness of the integrals of multivariate polynomials up to a given order, minimum average error, and quasi-random point sets. The performance of the different methods is tested in numerical experiments.



Denna post skapades 2017-07-27.
CPL Pubid: 250830

 

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Institutioner (Chalmers)

Institutionen för signaler och system, Signalbehandling (1900-2017)

Ämnesområden

Systemvetenskap, informationssystem och informatik
Elektroteknik och elektronik

Chalmers infrastruktur