Filtering of ultra-low electromagnetic detection signal using independent component analysis

Peijun Li, Huiran Jin, Benqin Song

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

The independent component analysis (ICA) was introduced for the filtering of the ultra-low electromagnetic (ULEM) detection curves. Simulated datasets were first used to validate the effectiveness of ICA in the filtering. The real datasets were then used to evaluate and compare the performance of the proposed filtering method. The results show that filtering of the ULEM signals based on ICA is feasible. Moreover, the proposed filtering method could effectively suppress the noise and enhance the valuable features of the curves, which facilitates geological interpretation of the resulting curves. Some issues are also discussed.

Original languageEnglish (US)
Pages (from-to)621-627
Number of pages7
JournalBeijing Daxue Xuebao (Ziran Kexue Ban)/Acta Scientiarum Naturalium Universitatis Pekinensis
Volume45
Issue number4
StatePublished - Jul 1 2009
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • General

Keywords

  • Coal-bed methane
  • Filtering
  • Independent component analysis
  • Ultra-low electromagnetic detection

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