Data Approximation with Time-Frequency Invariant Systems
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Autores: Davide Barbieri, Carlos A. Cabrelli, Eugenio Hernández Rodríguez
, Ursula M. Molter
- Localización: Landscapes of Time-Frequency Analysis: ATFA 2019 / coord. por Paolo Boggiatto, 2020, ISBN 978-3-030-56005-8, págs. 29-42
- Idioma: inglés
- Enlaces
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Resumen
In this paper we prove the existence of a time-frequency space that best approximates a given finite set of data. Here best approximation is in the least square sense, among all time-frequency spaces with no more than a prescribed number of generators. We provide a formula to construct the generators from the data and give the exact error of approximation. The setting is in the space of square integrable functions defined on a second countable LCA group and we use the Zak transform as the main tool.
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