Weighted Radial Basis Collocation Method for the Nonlinear Inverse Helmholtz Problems

In this paper, a meshfree weighted radial basis collocation method associated with the Newton's iteration method is introduced to solve the nonlinear inverse Helmholtz problems for identifying the parameter. All the measurement data can be included in the least-squares solution, which can avoid the iteration calculations for comparing the solutions with part of the measurement data in the Galerkin-based methods. Appropriate weights are imposed on the boundary conditions and measurement conditions to balance the errors, which leads to the high accuracy and optimal convergence for solving the inverse problems. Moreover, it is quite easy to extend the solution process of the one-dimensional inverse problem to high-dimensional inverse problem. Nonlinear numerical examples include one-, two- and three-dimensional inverse Helmholtz problems of constant and varying parameter identification in regular and irregular domains and show the high accuracy and exponential convergence of the presented method.

Automated summary

In this paper, a meshfree weighted radial basis collocation method associated with the Newton's iteration method is introduced to solve the nonlinear inverse Helmholtz problems for identifying the parameter. All measurement data are included in the least-squares solution to avoid the iteration calculations in Galerkin-based methods. Appropriate weights are imposed on the boundary and measurement conditions to balance the errors, resulting in high accuracy and optimal convergence for solving inverse problems. Moreover, the one-dimensional inverse problem can be easily extended to high-dimensional problems.