Seitenbereiche:



Zusatzinformationen:

FUN-Veranstaltungen

FoFö-Stammtisch, 23. November 2017, 14 Uhr siehe Info-Veranstaltungen

Kontakt

Abteilung Forschungsunterstützung (FUN):
forschen@jku.at


Positionsanzeige:

Inhalt:

Forschungseinheiten

Aufsatz / Paper in SCI-Expanded-Zeitschrift

Numerical solution of the neural field equation in the two-dimensional case

Buckwar E., Lima P.: Numerical solution of the neural field equation in the two-dimensional case, in: SIAM Journal on Scientific Computing, Volume 37, Number 6, Page(s) B962–B979, 2015.

BibTeX

@ARTICLE{
title = {Numerical solution of the neural field equation in the two-dimensional case},
type = {Aufsatz / Paper in SCI-Expanded-Zeitschrift},
author = {Buckwar, Evelyn and Lima, Pedro},
language = {EN},
abstract = {We are concerned with the numerical solution of a class of integro-differential equations, known as neural field equations, which describe the large-scale dynamics of spatially structured networks of neurons. These equations have many applications in neuroscience and robotics. We describe a numerical method for the approximation of solutions in the two-dimensional case, including a space-dependent delay in the integrand function. Compared with known algorithms for this type of equation we propose a scheme with higher accuracy in the time discretization. Since computational efficiency is a key issue in this type of calculation, we use a new method for reducing the complexity of the algorithm. The convergence issues are discussed in detail and a number of numerical examples are presented, which illustrate the performance of the method. Read More: http://epubs.siam.org/doi/abs/10.1137/15M1022562?journalCode=sjoce3},
pages = {B962–B979},
publisher = {Society for Industrial and Applied Mathematics},
journal = {SIAM Journal on Scientific Computing},
volume = {37},
number = {6},
issn = {1064-8275},
year = {2015},
}

Details

Zusammenfassung: We are concerned with the numerical solution of a class of integro-differential equations, known as neural field equations, which describe the large-scale dynamics of spatially structured networks of neurons. These equations have many applications in neuroscience and robotics. We describe a numerical method for the approximation of solutions in the two-dimensional case, including a space-dependent delay in the integrand function. Compared with known algorithms for this type of equation we propose a scheme with higher accuracy in the time discretization. Since computational efficiency is a key issue in this type of calculation, we use a new method for reducing the complexity of the algorithm. The convergence issues are discussed in detail and a number of numerical examples are presented, which illustrate the performance of the method. Read More: http://epubs.siam.org/doi/abs/10.1137/15M1022562?journalCode=sjoce3

Journal: SIAM Journal on Scientific Computing
Volume: 37
Nummer: 6
Erscheinungsjahr: 2015
Seitenreferenz: B962–B979
Anzahl Seiten: 18
Verlag: Society for Industrial and Applied Mathematics
ISSN: 1064-8275
Reichweite: International

Beteiligte

AutorInnen / HerausgeberInnen: Univ.-Prof. Dr. Evelyn Buckwar, Dr. Pedro Lima

Forschungseinheiten der JKU:

Wissenschaftszweige: 101 Mathematik | 101014 Numerische Mathematik | 101018 Statistik | 101019 Stochastik | 101024 Wahrscheinlichkeitstheorie

Zurück Zurück