Predictive algorithms in dynamical sampling for burst-like forcing terms

In this paper, we consider the problem of recovery of a burst-like forcing term in an initial value problem (IVP) in the framework of dynamical sampling. We introduce an idea of using two particular classes of samplers that allow one to predict the solution of the IVP over a time interval without a...

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Vydané v:Applied and computational harmonic analysis Ročník 65; s. 322 - 347
Hlavní autori: Aldroubi, Akram, Huang, Longxiu, Kornelson, Keri, Krishtal, Ilya
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Elsevier Inc 01.07.2023
Predmet:
Continuous sampling
Forcing
Frames
Reconstruction
Sampling theory
Semigroups
Reconstruction
Frames
Sampling theory
Semigroups
46N99
Forcing
Continuous sampling
42C15
94O20
ISSN:1063-5203, 1096-603X
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Popis
Shrnutí:In this paper, we consider the problem of recovery of a burst-like forcing term in an initial value problem (IVP) in the framework of dynamical sampling. We introduce an idea of using two particular classes of samplers that allow one to predict the solution of the IVP over a time interval without a burst. This leads to two different algorithms that stably and accurately approximate the burst-like forcing term even in the presence of a measurement acquisition error and a large background source.
ISSN:1063-5203
1096-603X
DOI:10.1016/j.acha.2023.03.003