Abstract

In applications of inversion methods to real data, nonlinear inverse problems are often simplied to more easily solvable linearized inverse problems. By doing so one introduces an error made by the linearization. Nonlinear inverse methods are more accurate because the methods that are used are more correct from a physical
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