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Monte Carlo analysis of inverse problems

Mosegaard, Klaus; Sambridge, Malcolm


Monte Carlo methods have become important in analysis of nonlinear inverse problems where no analytical expression for the forward relation between data and model parameters is available, and where linearization is unsuccessful. In such cases a direct mathematical treatment is impossible, but the forward relation materializes itself as an algorithm allowing data to be calculated for any given model. Monte Carlo methods can be divided into two categories: the sampling methods and the...[Show more]

CollectionsANU Research Publications
Date published: 2002
Type: Journal article
Source: Inverse Problems
DOI: 10.1088/0266-5611/18/3/201


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