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| Titre: | Reproducing kernel Hilbert space method for the numerical solutions of fractional cancer tumor models |
| Auteur(s): | Attia, Nourhane
Akgül, Ali
Seba, Djamila
Nour, Abdelkader |
| Mots-clés: | Caputo fractional derivative
fractional cancer tumor models
Gram–Schmidt orthogonalization process
reproducing kernel Hilbert space method |
| Date de publication: | 2020 |
| Collection/Numéro: | Mathematical Methods in the Applied Sciences.;SPECIAL ISSUE PAPER |
| Résumé: | This research work is concerned with the new numerical solutions of some essential fractional cancer tumor models, which are investigated by using reproducing kernel Hilbert space method (RKHSM). The most valuable advantage of the RKHSM is its ease of use and its quick calculation to obtain the numerical solutions of the considered problem. We make use of the Caputo fractional derivative. Our main tools are reproducing kernel theory, some important Hilbert spaces, and a normal basis. We illustrate the high competency and capacity of the suggested approach through the convergence analysis. The computational results clearly show the superior performance of the RKHSM. |
| URI/URL: | https://doi.org/10.1002/mma.6940
https://onlinelibrary.wiley.com/doi/abs/10.1002/mma.6940
http://dlibrary.univ-boumerdes.dz:8080/handle/123456789/5939 |
| Collection(s) : | Publications Internationales
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