Journal Article

Selection of radio pulsar candidates using artificial neural networks

R. P. Eatough, N. Molkenthin, M. Kramer, A. Noutsos, M. J. Keith, B. W. Stappers and A. G. Lyne

in Monthly Notices of the Royal Astronomical Society

Published on behalf of The Royal Astronomical Society

Volume 407, issue 4, pages 2443-2450
Published in print October 2010 | ISSN: 0035-8711
Published online July 2010 | e-ISSN: 1365-2966 | DOI: http://dx.doi.org/10.1111/j.1365-2966.2010.17082.x
Selection of radio pulsar candidates using artificial neural networks

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Radio pulsar surveys are producing many more pulsar candidates than can be inspected by human experts in a practical length of time. Here we present a technique to automatically identify credible pulsar candidates from pulsar surveys using an artificial neural network. The technique has been applied to candidates from a recent re-analysis of the Parkes multi-beam pulsar survey resulting in the discovery of a previously unidentified pulsar.

Keywords: methods: data analysis; stars: neutron; pulsars: general

Journal Article.  5410 words.  Illustrated.

Subjects: Astronomy and Astrophysics

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