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Generalized cross-validation applied to a Newton-type algorithm formicrowave tomography,

机译:广义交叉验证适用于微波层析成像的牛顿型算法,

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Abstract: The non-linear inverse scattering problem, occurring in the field of microwave tomography for biomedical applications, is solved with the Newton-type iterative algorithm. This method allows the reconstruction of the complex permittivity of strongly inhomogeneous objects. An ill-conditioned system of linear equations is obtained at each iteration and is regularized using Tikhonov's method. The choice of regularization is crucial, specially when random error is present in the data. We investigate the Generalized Cross Validation method for choosing the regularization parameter. Numerical examples are given in the case of 2D TM inverse problems.!29
机译:摘要:用牛顿型迭代算法解决了微波层析成像在生物医学领域中出现的非线性逆散射问题。这种方法可以重建很不均匀的物体的复介电常数。在每次迭代中获得一个病态的线性方程组,并使用Tikhonov方法对其进行正则化。正则化的选择至关重要,特别是当数据中存在随机错误时。我们研究了用于选择正则化参数的广义交叉验证方法。在二维TM反问题的情况下,给出了数值示例!29

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