Supervised Radio Frequency Interference Detection with SNNs

Radio Frequency Interference (RFI) poses a significant challenge in radio astronomy, arising from terrestrial and celestial sources, disrupting observations conducted by radio telescopes. Addressing RFI involves intricate heuristic algorithms, manual examination, and, increasingly, machine learning...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	2024 International Conference on Neuromorphic Systems (ICONS) S. 102 - 109
Hauptverfasser:	Pritchard, Nicholas J., Wicenec, Andreas, Bennamoun, Mohammed, Dodson, Richard
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 30.07.2024
Schlagworte:	Accuracy Benchmark testing Encoding multi-variate time-series segmentation Network architecture neuromorphic computing Neuromorphic engineering Optimization Radio astronomy Radiofrequency interference Spiking neural networks supervised learning Telescopes
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!