2005
DOI: 10.1007/s00024-004-2617-z
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Estimation of the Source Time Function Based on Blind Deconvolution with Gaussian Mixtures

Abstract: It is demonstrated that the blind deconvolution method is fully capable of recovering the unknown Green's function and of estimating the source time functions from observed seismic data of small earthquakes. Based on the assumption of the Gaussian-mixture model of the Green's function, the newlyformulated algorithm is evaluated using synthetic seismic data along with those of the May 8, 1996 Mexico earthquake (M c ¼ 4.6). Since the estimated results closely match the theoretical input very well, the method is … Show more

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Cited by 5 publications
(3 citation statements)
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“…Another step forward for a more detailed study of the rock-fall dynamic mechanism would be to remove the propagation effects from the seismic records, using blind deconvolution methods (Liao andHuang, 2005, Sèbe et al, 2005).…”
Section: Discussionmentioning
confidence: 99%
“…Another step forward for a more detailed study of the rock-fall dynamic mechanism would be to remove the propagation effects from the seismic records, using blind deconvolution methods (Liao andHuang, 2005, Sèbe et al, 2005).…”
Section: Discussionmentioning
confidence: 99%
“…where } { i x is the reflectivity or the Green's function, } { i h is the seismic source time function which is possibly the non-minimum phase, } { i n models the noise, and * denotes convolution. The hybrid blind deconvolution method developed by Liao and Huang [9] is applied to calculate the source time function and Green's function spontaneously from the seismic data directly. There are two major processes contained in the hybrid blind deconvolution.…”
Section: Hybrid Blind Deconvolutionmentioning
confidence: 99%
“…The generalized blind deconvolution technique offered by Liao and Huang [8] is used to eliminate the ground roll effect effectively and identify the location of reflective signal of a seismic data. Liao and Huang [9] employed the blind deconvolution by Santamaria et al [5] in conjunction with the water level algorithm to find out the directivity from the apparent source time functions and judge the actual fault plane of the earthquake. Furthermore, Liao and Huang [10] developed a hybrid blind deconvolution (HBD) and combined the GA algorithm to invert the source process of the Alaska earthquake (2002) occurred at Denali fault.…”
Section: Introductionmentioning
confidence: 99%