A self-parametrizing partition model approach to tomographic inverse problems
Partition modelling is a statistical method for nonlinear regression and classification, and is particularly suited to dealing with spatially variable parameters. Previous applications include disease mapping in medical statistics. Here we extend this method to the seismic tomography problem. The procedure involves a dynamic parametrization for the model which is able to adapt to an uneven spatial distribution of the information on the model parameters contained in the observed data. The...[Show more]
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