Inversion algorithms numerically evaluate the mismatch between model and data to guide the search for minima in parameter spaces. In an alternative approach, the numerical evaluation of data misfit can be replaced by subjectively judging the solution’s quality. This widens the class of problems that can be treated within the framework of formal inverse theory—in particular, various geophysical/geological/geodynamic applications in which structural similarity between model and data determines the quality of the fit. In this situation, prior knowledge, experience, and even personal intuition are crucial. This approach also provides a simple way to include such expertise in more traditional numeric applications, e.g., to treat ambiguous problems and disregard geologically unfeasible solutions from the inverse search.
Criteria for the numerical evaluation of data recovery algorithms for analogue-information converters
