Title :
Radio frequency interference identification and mitigation in pulsar observations using machine learning techniques
Author :
McCarty, M. ; Doran, G. ; Lazio, T.J.W. ; Thompson, David R. ; Ford, J. ; Prestage, Richard
Author_Institution :
Nat. Radio Astron. Obs., Green Bank, WV, USA
Abstract :
Summary form only given. Pulsar observations with the Robert C. Byrd Green Bank Telescope (GBT), located in Green Bank, WV, aid researchers in understanding the basic building blocks of our existence - matter, energy, space, and time - and how they behave under extreme physical conditions. Pulsars, rapidly rotating neutron stars with clock-like timing precision, can provide insights into a rich variety of physics and astrophysics.
Keywords :
astronomy computing; learning (artificial intelligence); neutron stars; pulsars; radiofrequency interference; radiotelescopes; GBT; Green Bank; West Virginia; astrophysics; clock-like timing precision; green bank telescope; machine learning technique; pulsar observation; radio frequency interference identification; radio frequency interference mitigation; rapidly rotating neutron stars; Bandwidth; Green products; Laboratories; Propulsion; Radiofrequency interference; Timing; Training data;
Conference_Titel :
Radio Science Meeting (USNC-URSI NRSM), 2013 US National Committee of URSI National
Conference_Location :
Boulder, CO
Print_ISBN :
978-1-4673-4776-1
DOI :
10.1109/USNC-URSI-NRSM.2013.6524993