1994
DOI: 10.1111/j.1365-246x.1994.tb04680.x
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Modified frequency-wavenumber algorithm for regional seismograms using Filon's quadrature: modelling ofLgwaves in eastern North America

Abstract: S U M M A R YThe main focus of this study is to develop an efficient frequency-wavenumber code to synthesize high-frequency (say, 10 Hz) regional seismograms (up to a distance of more than 1000 km) in a medium consisting of a large number of crustal layers, and investigate effects of regional waveguides on L, waves. In this newly developed code, the frequency-wavenumber response is evaluated by using the Filon's quadrature at high frequency and the polynomial approximation of Bessei's functions (implementing t… Show more

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Cited by 255 publications
(178 citation statements)
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References 30 publications
(26 reference statements)
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“…Because this numerical implementation differs from the FKRPROG software (Saikia, 1994) used to generate Green's functions, variance reductions of waveform fits of synthetic data generated with the reflectivity method may not reach 100%. The synthetic seismograms were filtered with the same band-pass filters applied to the data.…”
Section: Source Discriminationmentioning
confidence: 99%
See 1 more Smart Citation
“…Because this numerical implementation differs from the FKRPROG software (Saikia, 1994) used to generate Green's functions, variance reductions of waveform fits of synthetic data generated with the reflectivity method may not reach 100%. The synthetic seismograms were filtered with the same band-pass filters applied to the data.…”
Section: Source Discriminationmentioning
confidence: 99%
“…As discussed in the following section, this is a good approximation to the velocity model of the glacier. The Green's functions were computed using the FKRPROG software developed by Chandan Saikia of URS (Saikia, 1994). The deviatoric-and full-moment tensor solutions were calculated by applying a corrected form (Minson et al, 2007) of the linear time domain moment tensor inversion scheme used by Dreger et al (2000) and Dreger and Woods (2002).…”
Section: Moment Tensor Inversions Numerical Toolsmentioning
confidence: 99%
“…A Laplacian-smoothing operator, slip positivity, and a scalar moment minimization constraint is applied to stabilize the inversions. Green's functions based on the Novotný et al (2001) velocity profile, shown to be effective in modelling regional wave propagation, were used to invert the seismic waveforms, and were calculated using the frequency-wavenumber integration method (Saikia, 1994) for 1-km intervals in distance and 1-km intervals in depth. The source model used is a single fault plane with constant rupture velocity and constant dislocation rise time.…”
Section: Methodsmentioning
confidence: 99%
“…Prior to the inversion, full broadband waveforms of the three recorded components were band-pass filtered between 0.02-0.08 Hz or 0.05-0.10 Hz depending on the magnitude of the event and the signal-to-noise ratio of the waveforms. Theoretical Green's functions required to model the propagation of the seismic waves were constructed with the method and code described by Saikia (1994) using the velocity model of Novotný et al (2001), which has proven to successfully describe low frequency wave propagation (e.g., Roumelioti et al,2010;Kiratzi, 2010, 2011 andreferences therein). In Figure 2 we show the moment tensor solution and the waveform fit for the mainshock, while the parameters of the computed focal mechanisms of the aftershocks are listed in …”
Section: XLVII No 3 -1140mentioning
confidence: 99%
“…From that moment it was quite easy to use the regional waveforms and the produced synthetic ones to calculate source parameters through a linear inversion procedure. One of the inversion methods is the frequency-wavenumber (F-K) integration method (Saikia, 1994;Zeng & Anderson, 1995;Bouchon, 2003). This method which is applied in the present study mainly for moderate earthquakes, calculates synthetic waves directly compared with the observed ones for a given velocity structure.…”
Section: Regional Moment Tensor Inversionmentioning
confidence: 99%