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Neural Computing and Applications
Erschienen in: Neural Computing and Applications 7/2019

30.08.2017 | Original Article

A reproducing kernel Hilbert space pseudospectral method for numerical investigation of a two-dimensional capillary formation model in tumor angiogenesis problem

verfasst von: M. Emamjome, B. Azarnavid, H. Roohani Ghehsareh

Erschienen in: Neural Computing and Applications | Ausgabe 7/2019

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Abstract

In the current work, an interesting and challenging mathematical model for a two-dimensional capillary formation model in tumor angiogenesis problem will be investigated numerically. The mathematical model describes progression of tumor angiogenic factor in a unit square space domain, namely the extracellular matrix. An efficient numerical technique is performed to approximate the numerical solution of the governing practical model. The method is based on reproducing kernel Hilbert spaces in the framework of the standard pseudospectral method. Using reproducing kernel Hilbert space operational matrices and elimination the treatment of complicated boundary conditions are the main advantages of the proposed method. Some illustrative examples are included to demonstrate the effectiveness and versatility of the technique to deal with the governing mathematical model in both linear and nonlinear models .
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Metadaten
Titel
A reproducing kernel Hilbert space pseudospectral method for numerical investigation of a two-dimensional capillary formation model in tumor angiogenesis problem
verfasst von
M. Emamjome
B. Azarnavid
H. Roohani Ghehsareh
Publikationsdatum
30.08.2017
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 7/2019
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-017-3184-4

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