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The mutual information (MI) of Poisson-type channels has been linked to a filtering problem since the 70s, but its evaluation for specific continuous-time, discrete-state systems remains a demanding task. As an advantage, Markov renewal processes (Mr
Externí odkaz:
http://arxiv.org/abs/2403.15221
Autor:
Engelmann, Nicolai, Koeppl, Heinz
Hidden semi-Markov Models (HSMM's) - while broadly in use - are restricted to a discrete and uniform time grid. They are thus not well suited to explain often irregularly spaced discrete event data from continuous-time phenomena. We show that non-sam
Externí odkaz:
http://arxiv.org/abs/2210.09058
Structured stochastic processes evolving in continuous time present a widely adopted framework to model phenomena occurring in nature and engineering. However, such models are often chosen to satisfy the Markov property to maintain tractability. One
Externí odkaz:
http://arxiv.org/abs/2007.00347
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Structured stochastic processes evolving in continuous time present a widely adopted framework to model phenomena occurring in nature and engineering. However, such models are often chosen to satisfy the Markov property to maintain tractability. One
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d7b75b429eb2c08ab21466cc104f8e35
Akademický článek
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Autor:
Kubaczka E; Department of Electrical Engineering and Information Technology, TU Darmstadt, Darmstadt, 64283, Germany., Gehri M; Department of Electrical Engineering and Information Technology, TU Darmstadt, Darmstadt, 64283, Germany., Marlhens JJM; Department of Electrical Engineering and Information Technology, TU Darmstadt, Darmstadt, 64283, Germany.; Graduate School Life Science Engineering, TU Darmstadt, Darmstadt, 64283, Germany., Schwarz T; Department of Electrical Engineering and Information Technology, TU Darmstadt, Darmstadt, 64283, Germany., Molderings M; Department of Electrical Engineering and Information Technology, TU Darmstadt, Darmstadt, 64283, Germany.; Graduate School Life Science Engineering, TU Darmstadt, Darmstadt, 64283, Germany., Engelmann N; Department of Electrical Engineering and Information Technology, TU Darmstadt, Darmstadt, 64283, Germany., Garcia HG; UC Berkeley,CA 924720, USA.; Department of Molecular and Cell Biology, UC Berkeley, CA 924720, USA.; Chan Zuckerberg Biohub, UC Berkeley, CA 924720, USA., Hochberger C; Department of Electrical Engineering and Information Technology, TU Darmstadt, Darmstadt, 64283, Germany.; Centre for Synthetic Biology, TU Darmstadt, Darmstadt, 64283, Germany., Koeppl H; Department of Electrical Engineering and Information Technology, TU Darmstadt, Darmstadt, 64283, Germany.; Centre for Synthetic Biology, TU Darmstadt, Darmstadt, 64283, Germany.
Publikováno v:
BioRxiv : the preprint server for biology [bioRxiv] 2024 Sep 24. Date of Electronic Publication: 2024 Sep 24.