A-optimal encoding weights for nonlinear inverse problems, with application to the Helmholtz inverse problem
A-optimal encoding weights for nonlinear inverse problems, with application to the Helmholtz inverse problem
The computational cost of solving an inverse problem governed by PDEs, using multiple experiments, increases linearly with the number of experiments. A recently proposed method to decrease this cost uses only a small number of random linear combinations of all experiments for solving the inverse problem. This approach applies to …