Topological Derivative for the Inverse Conductivity Problem: A Bayesian Approach
- 200 Downloads
The employment of topological derivative concept is considered to propose a new optimization algorithm for the inverse conductivity problem. Since this inverse problem is nonlinear and ill-posed it is necessary to incorporate a prior knowledge about the unknown conductivity. In particular, we apply the Bayes theorem to add the assumption that we have just one small ball-shaped inclusion, which must be at a certain distance from the boundary of the domain. As the main emphasis of this paper is to investigate numerically the proposed approach, we shall use the meshless method of fundamental solutions to present some numerical results.
KeywordsInverse conductivity problem Topological derivative Method of fundamental solutions Bayesian inversion
The first author would like to thank CNPq-Science without Borders program for the financial support in this research. The hospitality shown by the University of Leeds is also gratefully acknowledged. The comments made by the referee are gratefully acknowledged.
- 13.Idier, J. (ed.): Bayesian Approach to Inverse Problems, 381 pp. ISTE, London (2008)Google Scholar
- 17.Kaipio, J., Somersalo, E.: Statistical and Computational Inverse Problems, 339 pp. Springer, New York (2005)Google Scholar
- 24.Kozlov, V.A., Maz’ya, V.G., Movchan, A.B.: Asymptotic Analysis of Fields in Multi-Structures, 282 pp. Clarendon Press, Oxford (1999)Google Scholar
- 29.Novotny, A.A., Sokołowski, J.: Topological Derivatives in Shape Optimization, 412 pp. Springer, Berlin (2012)Google Scholar