非齐次随机热方程的柯西问题及其在逆随机源问题中的应用

IF 1.2 4区 数学 Q2 MATHEMATICS, APPLIED
Shuli Chen, Zewen Wang, Guo-Xin Chen
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引用次数: 1

摘要

本文考虑了非齐次随机热方程的柯西问题及其逆源问题,其中源项被假定为加性白噪声驱动。Cauchy问题(正问题)是确定随机温度场的位移,而所考虑的逆问题是重建随机源的统计性质,即随机源的均值和方差。建设性地证明了柯西问题具有唯一的温和解,该温和解用积分形式表示。然后将逆随机源问题化为两个典型不适定的Fredholm积分方程。为了得到稳定的反解,引入正则块Kaczmarz方法求解两个Fredholm积分方程。最后,通过数值实验验证了该方法的有效性和鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cauchy problem of non-homogenous stochastic heat equation and application to inverse random source problem
In this paper, a Cauchy problem of non-homogenous stochastic heat equation is considered together with its inverse source problem, where the source term is assumed to be driven by an additive white noise. The Cauchy problem (direct problem) is to determine the displacement of random temperature field, while the considered inverse problem is to reconstruct the statistical properties of the random source, i.e. the mean and variance of the random source. It is proved constructively that the Cauchy problem has a unique mild solution, which is expressed an integral form. Then the inverse random source problem is formulated into two Fredholm integral equations of the first kind, which are typically ill-posed. To obtain stable inverse solutions, the regularized block Kaczmarz method is introduced to solve the two Fredholm integral equations. Finally, numerical experiments are given to show that the proposed method is efficient and robust for reconstructing the statistical properties of the random source.
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来源期刊
Inverse Problems and Imaging
Inverse Problems and Imaging 数学-物理:数学物理
CiteScore
2.50
自引率
0.00%
发文量
55
审稿时长
>12 weeks
期刊介绍: Inverse Problems and Imaging publishes research articles of the highest quality that employ innovative mathematical and modeling techniques to study inverse and imaging problems arising in engineering and other sciences. Every published paper has a strong mathematical orientation employing methods from such areas as control theory, discrete mathematics, differential geometry, harmonic analysis, functional analysis, integral geometry, mathematical physics, numerical analysis, optimization, partial differential equations, and stochastic and statistical methods. The field of applications includes medical and other imaging, nondestructive testing, geophysical prospection and remote sensing as well as image analysis and image processing. This journal is committed to recording important new results in its field and will maintain the highest standards of innovation and quality. To be published in this journal, a paper must be correct, novel, nontrivial and of interest to a substantial number of researchers and readers.
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