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Oversampling and Donoho–Logan type theorems in model spaces

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DREW01 - Multivariate approximation, discretization, and sampling recovery

The aim of this talk is to extend two results from the Paley–Wiener setting to moregeneral model spaces. The first one is an analogue of the oversampling Shannon sampling formula.The second one is a version of the Donoho–Logan Large Sieve Theorem which is a quantitativeestimate of the embedding of the Paley–Wiener space into an $L^2(\mathbb{R}, \mu)$ space. This is joint work with A. Baranov, K. Kellay & M. Speckbacher

This talk is part of the Isaac Newton Institute Seminar Series series.

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