Wavelet Maxima Method for Identifying Singularities in Electromagnetic Signal

Bing Han, Ji Tang, Guoze Zhao, Yaxin Bi, Lifeng Wang, Yuanzhi Cheng

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)
43 Downloads (Pure)

Abstract

Wavelet maxima method as a kind of data mining method has been applied to earthquake study, which gives us a direct way to identify singularities of different time and frequencies in long term of observations. This paper introduces how to identify electromagnetic anomalies using the wavelet maxima, i.e. the wavelet coefficients are calculated by using continuous wavelet transform and then calculate the maximum value of wavelet coefficients in each scale and identify the singularities associated with the earthquake.
Original languageEnglish
Pages (from-to)765-779
JournalSeismology and Geology
Volume37
Issue number3
DOIs
Publication statusPublished (in print/issue) - 20 Sept 2015

Keywords

  • Wavelet
  • Singularity
  • Data mining
  • Earthquake

Fingerprint

Dive into the research topics of 'Wavelet Maxima Method for Identifying Singularities in Electromagnetic Signal'. Together they form a unique fingerprint.

Cite this