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A Bayesian Deconvolution Approach for Receiver Function Analysis.
- Source :
-
IEEE Transactions on Geoscience & Remote Sensing . Dec2010, Vol. 48 Issue 12, p4151-4163. 13p. - Publication Year :
- 2010
-
Abstract
- In this paper, we propose a Bayesian methodology for receiver function analysis, a key tool in determining the deep structure of the Earth's crust. We exploit the assumption of sparsity for receiver functions to develop a Bayesian deconvolution method as an alternative to the widely used iterative deconvolution. We model samples of a sparse signal as i.i.d. Student-t random variables. Gibbs sampling and variational Bayes techniques are investigated for our specific posterior inference problem. We used those techniques within the expectation-maximization (EM) algorithm to estimate our unknown model parameters. The superiority of the Bayesian deconvolution is demonstrated by the experiments on both simulated and real earthquake data. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 01962892
- Volume :
- 48
- Issue :
- 12
- Database :
- Academic Search Index
- Journal :
- IEEE Transactions on Geoscience & Remote Sensing
- Publication Type :
- Academic Journal
- Accession number :
- 62331882
- Full Text :
- https://doi.org/10.1109/TGRS.2010.2050327