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The Generalized Fibonacci Grid as Low-Discrepancy Point Set for Optimal Deterministic Gaussian Sampling

Frisch, Daniel ORCID iD icon 1; Hanebeck, Uwe D. 1
1 Institut für Anthropomatik und Robotik (IAR), Karlsruher Institut für Technologie (KIT)

Abstract:

We propose a multivariate Gaussian sampling scheme. The samples exhibit an “optimal deterministic” configuration. This entails better quadrature or cubature results than with random or quasi-random samples. Our sampling is based on the generalized Fibonacci grid that makes there markable properties of the well-known two-dimensional Fibonacci grid applicable in higher dimensions. Two options for generating the multivariate generalized Fibonacci grid are presented, based on a rotated grid and a linear programming counter, respectively. Various options for covariance matching are explored to obtain an unscented transform.


Volltext §
DOI: 10.5445/IR/1000192555
Veröffentlicht am 23.04.2026
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Anthropomatik und Robotik (IAR)
Publikationstyp Vortrag
Publikationsdatum 05.07.2024
Sprache Englisch
Identifikator KITopen-ID: 1000192555
Veranstaltung 27th International Conference on Information Fusion (FUSION 2024), Venedig, Italien, 08.07.2024 – 11.07.2024
Bemerkung zur Veröffentlichung Slides of conference presentation of journal paper with KITopen-ID:1000167375 and URL:https://isif.org/media/generalized-fibonacci-grid-low-discrepancy-point-set-optimal-deterministic-gaussian-sampling
Externe Relationen Siehe auch
Schlagwörter deterministic sampling, orthogonal inverse transform sampling, Gaussian sampling, nonlinear estimation
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