CORDIS Project
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This project focuses on developing mathematical methods for approximating scattered data to enhance algorithms in signal processing. It explores new models that consider irregular sampling points, aiming to improve function reconstruction across various dimensions.
We will develop mathematical methods for scattered data approximation that can be used to implement efficient algorithms in signal processing and related areas.
So far, the problem of reconstructing an unknown function from a given discrete set of sampling points has been studied in shift invariant spaces, i.e. spaces generated by translates of a function (or finitely many functions).
We propose to consider the problem in spaces generated by translates of compressed copies of a function (or fini…
UNIVERSITAT WIEN
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