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Dokumenttyp:
Konferenzbeitrag
Autor(en):
Hanebeck, Ariane; Czado, Claudia
Titel:
On the Observability of Gaussian Models using Discrete Density Approximations
Abstract:
This paper proposes a novel method for testing observability in Gaussian models using discrete density approximations (deterministic samples) of (multivariate) Gaussians. Our notion of observability is defined by the existence of the maximum a posteriori estimator. In the first step of the proposed algorithm, the discrete density approximations are used to generate a single representative design observation vector to test for observability. In the second step, a number of carefully chosen design...    »
Dewey-Dezimalklassifikation:
510 Mathematik
Kongress- / Buchtitel:
2022 25th International Conference on Information Fusion (FUSION)
Band / Teilband / Volume:
2022 25th International Conference on Information Fusion (FUSION)
Datum der Konferenz:
04 - 07 July 2022
Verlag / Institution:
IEEE
Publikationsdatum:
04.07.2022
Jahr:
2022
Quartal:
3. Quartal
Jahr / Monat:
2022-07
Monat:
Jul
Print-ISBN:
978-1-6654-8941-6 Print on Demand(PoD)
E-ISBN:
978-1-7377497-2-1
Sprache:
en
Erscheinungsform:
WWW
Volltext / DOI:
doi:10.23919/fusion49751.2022.9841251
WWW:
IEEE Xplore
Semester:
SS 22
TUM Einrichtung:
Professur für Angewandte Mathematische Statistik
Format:
Text
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