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Inverse time-dependent source problems for the heat equation with nonlocal boundary conditions

机译:具有非识别边界条件的热方程的逆时间源问题

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In this paper, we consider inverse problems of finding the time-dependent source function for the population model with population density nonlocal boundary conditions and an integral over-determination measurement. These problems arise in mathematical biology and have never been investigated in the literature in the forms proposed, although related studies do exist. The unique solvability of the inverse problems are rigorously proved using generalized Fourier series and the theory of Volterra integral equations. Continuous dependence on smooth input data also holds but, as in reality noisy errors are random and non-smooth, the inverse problems are still practically ill-posed. The degree of ill-posedness is characterised by the numerical differentiation of a noisy function. In the numerical process, the boundary element method together with either a smoothing spline regularization or the first-order Tikhonov regularization are employed with various choices of regularization parameter. One is based on the discrepancy principle and another one is the generalized cross-validation criterion. Numerical results for some benchmark test examples are presented and discussed in order to illustrate the accuracy and stability of the numerical inversion. (C) 2018 Elsevier Inc. All rights reserved.
机译:在本文中,我们考虑在人口密度非局部边界条件和积分过度测量中找到人口模型的时间依赖源功能的逆问题。这些问题在数学生物学中出现,并且从未在提出的形式中在文献中进行了调查,尽管存在相关的研究确实存在。使用广义傅里叶系列和Volterra Integral方程理论严格证明了逆问题的独特可解性。持续依赖性对平滑输入数据也保持,但是,如现实中的错误是随机而非平滑的,逆问题仍然没有释放。不良呈现程度的特征在于噪声功能的数值分化。在数值过程中,边界元方法与平滑花键正则化或一阶Tikhonov正则化与正则化参数的各种选择一起使用。一个是基于差异原理,另一个是广义交叉验证标准。呈现和讨论了一些基准测试示例的数值结果,以说明数值反演的精度和稳定性。 (c)2018年Elsevier Inc.保留所有权利。

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