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Computer Science > Information Theory

arXiv:2109.00623 (cs)
[Submitted on 1 Sep 2021]

Title:Predictive algorithms in dynamical sampling for burst-like forcing terms

Authors:Akram Aldroubi, Longxiu Huang, Keri Kornelson, Ilya Krishtal
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Abstract: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.
Subjects: Information Theory (cs.IT); Dynamical Systems (math.DS)
Cite as: arXiv:2109.00623 [cs.IT]
  (or arXiv:2109.00623v1 [cs.IT] for this version)
  https://doi.org/10.48550/arXiv.2109.00623

Submission history

From: Longxiu Huang [view email]
[v1] Wed, 1 Sep 2021 21:34:52 UTC (1,282 KB)
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