The Gel'fand-Levitan-Krein method and the globally convergent method for experimental data
classification
🧮 math-ph
math.MP
keywords
methodcomparisonconvergentdataexperimentalfand-levitan-kreingloballynumerical
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Comparison of numerical performances of two methods for coefficient inverse problems is described. The first one is the classical Gel'fand-Levitan-Krein equation method, and the second one is the recently developed approximately globally convergent numerical method. This comparison is performed for both computationally simulated and experimental data.
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