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arXiv 2108.02999math.NAcs.NA
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小分数阶Caputo导数的快速算法及误差分析

Fast Algorithms and Error Analysis of Caputo Derivatives with Small Factional Orders

Zihang Zhang, Qiwei Zhan, Zhennan Zhou

摘要:

在本文中,我们研究快速算法在小分数阶制度,以近似的Caputo导数$^C_0D_t^αu(t)$时,$α$是小的。我们重点研究了两种快速算法,即FIR和FIDR,它们都依赖于指数逼近的和,以减少评估历史部分的成本。FIR是最初在[16]中提出的数值格式,而FIDR是在[26]中提出的替代方案,并且我们证明了当$α$较小时,后者更优越。通过定量估计,我们证明了在给定一定的误差阈值的情况下,随着$α$变小,计算Caputo导数的历史部分的计算成本可以降低。因此,在小的$α$方案中仅需要用于快速评估的最小成本,这与工程实践中的主流协议相匹配。我们还提出了改进的稳定性和误差分析的FIDR求解线性分数阶扩散方程,它实现了明确的依赖于分数阶$α$的误差界。最后,我们进行了系统的数值研究的FIR和FIDR计划的性能,在那里我们探索的准确性和效率之间的权衡时,$α$是小的。

英文摘要:

In this paper, we investigate fast algorithms in the small fraction order regime to approximate the Caputo derivative $^C_0D_t^αu(t)$ when $α$ is small. We focus on two fast algorithms, i.e. FIR and FIDR, both relying on the sum-of-exponential approximation to reduce the cost of evaluating the history part. FIR is the numerical scheme originally proposed in [16], and FIDR is an alternative scheme proposed in [26], and we show that the latter is superior when $α$ is small. With quantitative estimates, we prove that given a certain error threshold, the computational cost of evaluating the history part of the Caputo derivative can be decreased as $α$ gets small. Hence, only minimal cost for the fast evaluation is required in the small $α$ regime, which matches prevailing protocols in engineering practice. We also present improved stability and error analysis of FIDR for solving linear fractional diffusion equations, which achieves clear dependence of the error bound on the fraction order $α$. Finally, we carry out systematic numerical studies for the performances of both FIR and FIDR schemes, where we explore the trade-off between accuracy and efficiency when $α$ is small.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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