Nonlinear Processes in Geophysics
Nonlinear Processes in Geophysics
NPG
Articles | Volume 26, issue 1
Articles | Volume 26, issue 1
https://doi.org/10.5194/npg-26-13-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/npg-26-13-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 26, issue 1
Research article
 | 
01 Mar 2019
Research article |  | 01 Mar 2019

Denoising stacked autoencoders for transient electromagnetic signal denoising

Fanqiang Lin, Kecheng Chen, Xuben Wang, Hui Cao, Danlei Chen, and Fanzeng Chen

Viewed

Total article views: 4,896 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
3,400 1,344 152 4,896 210 256
  • HTML: 3,400
  • PDF: 1,344
  • XML: 152
  • Total: 4,896
  • BibTeX: 210
  • EndNote: 256
Views and downloads (calculated since 02 Oct 2018)
Cumulative views and downloads (calculated since 02 Oct 2018)

Viewed (geographical distribution)

Total article views: 4,896 (including HTML, PDF, and XML) Thereof 4,243 with geography defined and 653 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 04 Apr 2026
Download
Short summary
The deep-seated information is reflected in the late-stage data of the second field. By introducing the deep learning algorithm integrated with the characteristics of the secondary field data, we can map the contaminated data in late track data to a high-probability position. By comparing several filtering algorithms, the SFSDSA method has better performance and the denoising signal is conducive to further improving the effective detection depth.
Read more
Share