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2012MNRAS.427.1052B - Mon. Not. R. Astron. Soc., 427, 1052-1065 (2012/December-1)
The High Time Resolution Universe Pulsar Survey - VI. An artificial neural network and timing of 75 pulsars.
BATES S.D., BAILES M., BARSDELL B.R., BHAT N.D.R., BURGAY M., BURKE-SPOLAOR S., CHAMPION D.J., COSTER P., D'AMICO N., JAMESON A., JOHNSTON S., KEITH M.J., KRAMER M., LEVIN L., LYNE A., MILIA S., NG C., NIETNER C., POSSENTI A., STAPPERS B., THORNTON D. and VAN STRATEN W.
Abstract (from CDS):
In the second half of the paper we discuss the development and application of an artificial neural network in the data-processing pipeline for the survey. We discuss the tests that were used to generate scores and find that our neural network was able to reject over 99per cent of the candidates produced in the data processing, and able to blindly detect 85per cent of pulsars. We suggest that improvements to the accuracy should be possible if further care is taken when training an artificial neural network; for example, ensuring that a representative sample of the pulsar population is used during the training process, or the use of different artificial neural networks for the detection of different types of pulsars.
Abstract Copyright: © 2012 The Authors Monthly Notices of the Royal Astronomical Society © 2012 RAS
Journal keyword(s): methods: data analysis - stars: neutron - pulsars: general
VizieR on-line data: <Available at CDS (J/MNRAS/427/1052): table3.dat table4.dat tablea1.dat>
Simbad objects: 72
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