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The pre/post equilibrated conditioning methods to solve Cauchy problems

机译:解决柯西问题的前后平衡调理方法

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In the present paper, the inverse Cauchy problems of Laplace equation and biharmonic equation are transformed, by using the method of fundamental solutions (MFS) and the Trefftz method (TM), to the systems of linear equations for determining the expansion coefficients. Then, we propose three different conditioners together with the conjugate gradient method (CGM) to solve the resultant ill-posed linear systems. They are the post-conditioning CGM and the pre-conditioning CGM based on the idea of equilibrated norm for the conditioned matrices, as well as a minimum-distance conditioner. These algorithms are convergent fast and accurate by solving the inverse Cauchy problems under random noise.
机译:本文采用基本解法(MFS)和特雷夫兹法(TM),将拉普拉斯方程和双调和方程的柯西逆问题转化为线性方程组,以确定膨胀系数。然后,我们提出了三种不同的调节器以及共轭梯度法(CGM)来解决由此产生的不适定线性系统。它们是基于条件矩阵均衡范式思想的后条件CGM和条件CGM,以及最小距离条件器。通过解决随机噪声下的柯西逆问题,这些算法可以快速,准确地收敛。

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