Article ISI
2021 IEEE IFAC INTERNATIONAL CONFERENCE ON AUTOMATION/XXIV CONGRESS OF THE CHILEAN ASSOCIATION OF AUTOMATIC CONTROL (IEEE IFAC ICA - ACCA2021)  (2021)

Adaptive Digital Filter using NARX Deep Neural Networks for ground-based observatories

Toledo-Mercado, Esteban; Soto, Ismael; Rojo, Patricio M.; Pereira-Mendoza, Jonathan; Quiroz, Juan; Zamorano-Illanes, Raul; IEEE

Abstract

In this paper we will present a new method based on the non-symmetry of the wavelength distributions of exoplanet transits. By the clustering of wavelengths with similar behaviour, it is possible to cancel terrestrial atmospheric turbulence at ground-based observatories. Two types of benchmarks for training the NARX neural network are presented. Complexity and performance studies using transient spectroscopy data from the WASP-19b system are also included.

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Título según WOS: Adaptive Digital Filter using NARX Deep Neural Networks for ground-based observatories
Título de la Revista: 2021 IEEE IFAC INTERNATIONAL CONFERENCE ON AUTOMATION/XXIV CONGRESS OF THE CHILEAN ASSOCIATION OF AUTOMATIC CONTROL (IEEE IFAC ICA - ACCA2021)
Editorial: IEEE
Fecha de publicación: 2021
DOI:

10.1109/ICAACCA51523.2021.9465196
Notas: ISI