A new version of the convexification method for a 1-D coefficient inverse problem with experimental data
This work improves the convexification method for coefficient inverse problems, making it more practical by removing a problematic component, though it is incremental and domain-specific.
The authors developed a new version of the convexification method for a 1-D coefficient inverse problem that eliminates the need for a 'tail function', proving global convergence of the gradient projection method and demonstrating effectiveness on both simulated and experimental data.
A new version of the convexification method is developed analytically and tested numerically for a 1-D coefficient inverse problem in the frequency domain. Unlike the previous version, this one does not use the so-called "tail function", which is a complement of a certain truncated integral with respect to the wave number. Globally strictly convex cost functional is constructed with the Carleman Weight Function. Global convergence of the gradient projection method to the correct solution is proved. Numerical tests are conducted for both computationally simulated and experimental data.