Novelty Detection on Radio Astronomy Data using Signatures

arXiv:2402.14892v1 Announce Type: cross
Abstract: We introduce SigNova, a new semi-supervised framework for detecting anomalies in streamed data. While our initial examples focus on detecting radio-frequency interference (RFI) in digitized signals within the field of radio astronomy, it is important to note that SigNova's applicability extends to any type of streamed data. The framework comprises three primary components. Firstly, we use the signature transform to extract a canonical collection of summary statistics from observational sequences. This allows us to represent …

abstract arxiv astronomy astro-ph.im cs.lg data detection examples focus framework interference radio semi-supervised type