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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Bibliographic Details
Published in:Applied and computational harmonic analysis Vol. 65; pp. 322 - 347
Main Authors: Aldroubi, Akram, Huang, Longxiu, Kornelson, Keri, Krishtal, Ilya
Format: Journal Article
Language:English
Published: Elsevier Inc 01.07.2023
Subjects:
Continuous sampling
Forcing
Frames
Reconstruction
Sampling theory
Semigroups
Reconstruction
Frames
Sampling theory
Semigroups
46N99
Forcing
Continuous sampling
42C15
94O20
ISSN:1063-5203, 1096-603X
Online Access:Get full text
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Summary: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