68
Views
6
CrossRef citations to date
0
Altmetric
Original Articles

Non-linear integral equations for the complete electrode model in inverse impedance tomography

&
Pages 1267-1288 | Received 29 Feb 2008, Accepted 04 Mar 2008, Published online: 23 Dec 2008
 

Abstract

We consider the two-dimensional inverse electrical impedance problem for piecewise constant conductivities with the data given in terms of the complete electrode model. Our approach is based on a system of non-linear integral equations arising from Green's representation formula from which the unknown conductivities and the unknown shapes of the interfaces are obtained iteratively via linearization. The method is an extension of our previous work for the case of classical data in terms of full Cauchy data on ∂D. This in turn originated from a method that has been suggested by Kress and Rundell for the case of a perfectly conducting inclusion. For the choice of the regularization parameters occurring in the algorithm, we propose an evolutionary algorithm and the initial guess for the iterations is obtained through employing a Newton-type finite element method. We describe the method in detail and illustrate its feasibility by numerical examples.

Acknowledgements

The research of H.E. was supported by the German Research Foundation DFG through the Graduiertenkolleg Identification in Mathematical Models and by the German Federal Ministry of Education and Research BMBF through the joint research project Regularization in Electrical Impedance Tomography.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 1,361.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.