Fundamental kernel-based method for backward space-time fractional diffusion problem

Fundamental kernel-based method for backward space-time fractional diffusion problem
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后向时空分数扩散问题的基本核方法

DOI:
10.1016/j.camwa.2015.11.023
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发表时间:
2016
影响因子:
2.9
通讯作者:
Hon Y. C.
Hon Y. C.
中科院分区:
数学2区
文献类型:
--
作者:
Dou Fangfang;Hon Y. C.

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基于核近似技术,本文设计了一种求解后向时空分数阶扩散问题(BSTFDP)的高效、精确的数值格式。近似中使用的核是时空分数阶扩散方程的基本解,用Mittag-Leffler函数的傅里叶逆变换表示。快速傅里叶逆变换(IFFT)技术的使用,使一个准确和有效的评估的基本解决方案,并给出了一个强大的数值算法的解决方案的BSTFDP。由于BSTFDP是内在不适定的,我们采用标准的Tikhonov正则化技术,以获得一个稳定的解决方案,高度病态的线性方程组的结果系统。为了选择最佳的正则化参数,我们联合收割机的正则化技术与广义交叉验证(GCV)方法的源点的最佳位置在使用的基本解决方案。同时,该算法还加快了Dou和Hon(2014)给出的先前方法。数值算例验证了该方法的准确性和有效性。
Based on kernel-based approximation technique, we devise in this paper an efficient and accurate numerical scheme for solving a backward space–time fractional diffusion problem (BSTFDP). The kernels used in the approximation are the fundamental solutions of the space–time fractional diffusion equation expressed in terms of inverse Fourier transform of Mittag-Leffler functions. The use of Inverse fast Fourier transform (IFFT) technique enables an accurate and efficient evaluation of the fundamental solutions and gives a robust numerical algorithm for the solution of the BSTFDP. Since the BSTFDP is intrinsic ill-posed, we apply the standard Tikhonov regularization technique to obtain a stable solution to the highly ill-conditioned resultant system of linear equations. For choosing optimal regularization parameter, we combine the regularization technique with the generalized cross validation (GCV) method for an optimal placement of the source points in the use of fundamental solutions. Meanwhile, the proposed algorithm also speeds up the previous method given in Dou and Hon (2014). Several numerical examples are constructed to verify the accuracy and efficiency of the proposed method.
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