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Title:

On the Observability of Gaussian Models using Discrete Density Approximations

Document type:
Konferenzbeitrag
Author(s):
Hanebeck, Ariane; Czado, Claudia
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 Decimal Classification:
510 Mathematik
Book / Congress title:
2022 25th International Conference on Information Fusion (FUSION)
Volume:
2022 25th International Conference on Information Fusion (FUSION)
Date of congress:
04 - 07 July 2022
Publisher:
IEEE
Date of publication:
04.07.2022
Year:
2022
Quarter:
3. Quartal
Year / month:
2022-07
Month:
Jul
Print-ISBN:
978-1-6654-8941-6 Print on Demand(PoD)
E-ISBN:
978-1-7377497-2-1
Language:
en
Publication format:
WWW
Fulltext / DOI:
doi:10.23919/fusion49751.2022.9841251
WWW:
IEEE Xplore
Semester:
SS 22
TUM Institution:
Professur für Angewandte Mathematische Statistik
Format:
Text
 BibTeX