Selection of radio pulsar candidates using artificial neural networks

Research output: Contribution to journalArticle

  • External authors:
  • R. P. Eatough
  • N. Molkenthin
  • M. Kramer
  • A. Noutsos
  • B. W. Stappers
  • A. G. Lyne


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. © 2010 The Authors. Journal compilation. © 2010 RAS.

Bibliographical metadata

Original languageEnglish
Pages (from-to)2443-2450
Number of pages7
JournalMonthly Notices of the Royal Astronomical Society
Issue number4
Publication statusPublished - Oct 2010