A method for pulsar searching: combining a two-dimensional autocorrelation profile map and a deep convolutional neural network

@article{Wang2021AMF,
  title={A method for pulsar searching: combining a two-dimensional autocorrelation profile map and a deep convolutional neural network},
  author={Longqi Wang and Jing Jin and Lu Liu and Yi Shen},
  journal={Research in Astronomy and Astrophysics},
  year={2021},
  volume={21}
}
In pulsar astronomy, detecting effective pulsar signals among numerous pulsar candidates is an important research topic. Starting from space X-ray pulsar signals, the two-dimensional autocorrelation profile map (2D-APM) feature modelling method, which utilizes epoch folding of the autocorrelation function of X-ray signals and expands the time-domain information of the periodic axis, is proposed. A uniform setting criterion regarding the time resolution of the periodic axis addresses pulsar… 

A Pulsar Search Method Combining a New Feature Representation and Convolutional Neural Network

The radiation energy of X-ray pulsars is mainly concentrated in the high-energy ray bands, so processing high-energy photon signals is helpful for discovering some young and active pulsars. To

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