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Reshaping spectrum estimates by removing periodic noise: Application to seismic spectral ratios
Author(s) -
Lees Jonathan M.
Publication year - 1995
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1029/94gl03221
Subject(s) - deconvolution , spectral line , noise (video) , smoothing , attenuation , acoustics , signal (programming language) , background noise , spectral density , signal to noise ratio (imaging) , line (geometry) , seismic noise , computational physics , physics , computer science , optics , geology , mathematics , telecommunications , statistics , seismology , artificial intelligence , image (mathematics) , geometry , astronomy , programming language
An automated method for removing line spectrum elements embedded in colored spectra is presented. Since smooth spectrum estimates are desired, line spectra tend to smear out over an effective smoothing window. This introduces a bias in spectrum estimation that seriously degrades signal‐to‐noise ratios, spectral deconvolution or any other operation where spectrum shape is important. Multi‐taper analysis provides a simple algorithmic solution including a method of determining where spectral peaks are both significant with high power. The method is completely general, and examples include estimation of signal‐to‐noise ratio at the 1990 high frequency array, Pinyon Flat, CA. A comparison of noise spectra line segments and signal spectra line spectra reveals similarities associated with instrument noise and shallow resonances stimulated by incoming seismic signals. Identification and removal of resonances can provide a better means of estimating background noise spectra for modeling earthquake source spectra and path effects associated with attenuation.