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An inversion process is incomplete without an analysis of the errors in the constructed solutions. When dealing with inexact experimental data, a fundamental task is the determination of how close to the truth (if there is one !) or how representative of the real world our inverse solution is. To shed some light on this issue, we will examine how the experimental errors translate into errors in the model estimates and use the well developed tools of linear appraisal (Section 6) to estimate approximate reliability of the non-linear solutions.

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