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The philosophy of the approximate global convergence for multidimensional coefficient inverse problems

机译:多维系数逆问题的近似全局收敛原理

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Both the most important and the most challenging question in the numerical treatment of a multidimensional coefficient inverse problem for a partial differential equation is the following: How to obtain a point in a small neighbourhood of the exact solution without any a priori knowledge of this solution? The recent numerical experience of the authors shows that in order to develop a truly efficient algorithm addressing this question, it is necessary to make some reasonable approximations. Although these approximations cannot be rigorously justified, numerical studies show that corresponding algorithms work quite well. The authors call this approach 'approximate global convergence'. The goal of this article is to present a short illustrative review of this philosophy.
机译:在偏微分方程多维系数反问题的数值处理中,最重要和最具挑战性的问题如下:在没有先验知识的情况下,如何在精确解的小邻域中获得一个点?作者最近的数值经验表明,为了开发一种真正有效的算法来解决这个问题,有必要做出一些合理的近似。尽管不能严格证明这些近似值的正确性,但数值研究表明,相应的算法效果很好。作者称这种方法为“近似全局收敛”。本文的目的是提供对此哲学的简短说明性回顾。

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