Titlebook: Inverse Problems and Applications; Larisa Beilina Conference proceedings 2015 Springer International Publishing Switzerland 2015 Maxwell e

山羊

一條卷發(fā)

2194-1009 ed new methods for solving inverse problems.Applies methods ??This volume arose from the Third Annual Workshop on Inverse Problems, held in Stockholm on May 2-6, 2012. The proceedings present new analytical developments and numerical methods for solutions of? inverse and ill-posed problems, which co

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Methods of Quantitative Reconstruction of Shapes and Refractive Indices from Experimental data,get a good first approximation for the exact solution. Results of this stage are presented in [5, 14]. On the second stage the local adaptive finite element method of [1] is applied to refine the solution obtained on the first stage. In this chapter we briefly describe methods and present new results for both stages.

Alveoli

anatomical

地殼

Iteratively Regularized Gauss-Newton Methods under Random Noise,es of forming stochastic measurement data, establish approximation properties of the methods in the mean square sense and prove corresponding accuracy estimates The work is supported by the Russian Foundation for Basic Research (project no. 12–01–00239a).

Incompetent

On the Solution of Forward and Inverse Problems of Voltammetry,r efficiency strongly depends on the way of calculation of the forward problem. In this paper we formulate forward and inverse problems of voltammetry, then consider three different algorithms of solution of the voltammetry equation, including developed by author semi-analytical method.

neoplasm

Conference proceedings 2015ective numerical methods. The book highlights recent research focusing on reliable numerical techniques for the solution of inverse problems, with relevance to a range of fields including acoustics, electromagnetics, optics, medical imaging, and geophysics.??

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Iteratively Regularized Gauss-Newton Methods under Random Noise,pace. Perturbations of right-hand sides of equations are modeled by Hilbert space valued random elements. We analyze two qualitatively different schemes of forming stochastic measurement data, establish approximation properties of the methods in the mean square sense and prove corresponding accuracy

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