Jin, B;
Li, B;
Zhou, Z;
(2019)
Discrete maximal regularity of time-stepping schemes for fractional evolution equations.
Numerische Mathematik
, 22
(8)
pp. 871-875.
10.1007/s00211-017-0904-8.
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Abstract
In this work, we establish the maximal (Formula presented.)-regularity for several time stepping schemes for a fractional evolution model, which involves a fractional derivative of order (Formula presented.), (Formula presented.), in time. These schemes include convolution quadratures generated by backward Euler method and second-order backward difference formula, the L1 scheme, explicit Euler method and a fractional variant of the Crank–Nicolson method. The main tools for the analysis include operator-valued Fourier multiplier theorem due to Weis (Math Ann 319:735–758, 2001. doi:10.1007/PL00004457) and its discrete analogue due to Blunck (Stud Math 146:157–176, 2001. doi:10.4064/sm146-2-3). These results generalize the corresponding results for parabolic problems.
| Type: | Article |
|---|---|
| Title: | Discrete maximal regularity of time-stepping schemes for fractional evolution equations |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1007/s00211-017-0904-8 |
| Publisher version: | http://doi.org/10.1007/s00211-017-0904-8 |
| Language: | English |
| Additional information: | Copyright © 2017 The Author(s). This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
| Keywords: | Epidemiology, Athlete, Injury, Prevalence, Aging |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/1561159 |
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