On numerical simulations of integrate-and-fire neural networks

被引：156

作者：

Hansel, D ^{[1
]}

Mato, G

Meunier, C

Neltner, L

机构：

[1] Ecole Polytech, Ctr Phys Theor, CNRS, UPR014, F-91128 Palaiseau, France

[2] Comis Nacl Energia Atom, Ctr Atom Bariloche, RA-8400 Bariloche, Rio Negro, Argentina

来源：

NEURAL COMPUTATION | 1998年 / 10卷 / 02期

关键词：

D O I：

10.1162/089976698300017845

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

It is shown that very small time steps are required to reproduce correctly the synchronization properties of large networks of integrate-and-fire neurons when the differential system describing their dynamics is integrated with the standard Euler or second-order Runge-Kutta algorithms. The reason for that behavior is analyzed, and a simple improvement of these algorithms is proposed.

引用

页码：467 / 483

页数：17

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