Titlebook: Computational Electromagnetics and Model-Based Inversion; A Modern Paradigm fo Harold A Sabbagh,R. Kim Murphy,Jeremy S Knopp Book 2013 Spri

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NLSE: Parameter-Based Inversion Algorithmal problems. The basic inversion algorithm described in Chap. 11 was based upon the Gauss–Newton theory of nonlinear least-squares estimation and is called NLSE in this book. In this chapter we will develop the mathematical background of this theory more fully, because this algorithm will be the fou

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Robust Statistical Estimatorsst estimators in this chapter and give an example of the application of them to pre-processing some experimental data. Both of the robust estimators are taken from [63], and we closely follow those authors in our presentation.

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1434-8322 ficult, problems in eddy-current NDE. In fact, in many cases these methods are the only things available for solving the problems..The book will cover the topic of computational electromagnetics in eddy-current978-1-4899-8814-0978-1-4419-8429-6Series ISSN 1434-8322 Series E-ISSN 2198-2589

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https://doi.org/10.1007/978-3-658-00483-5chapter, we develop a theory that allows us to efficiently discretize the current density in such probes, thereby allowing us to use transfer matrices (these will be discussed in Chap. 10) and similar mathematical constructs for solving problems.

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https://doi.org/10.1007/978-3-658-40103-0ally large bodies using boundary-integral equations. As far as we know, we are the first to apply the “spatial decomposition algorithm” to the solution of three-dimensional scattering problems when the scatterer (the “flaw”) occupies several regions with different electrical properties using volume-integral equations.