Geodesic
Principles of constructing layered neural networks based on pulse neurons
Modelirovanie i analiz informacionnyh sistem, Tome 18 (2011) no. 2, pp. 65-76 Cet article a éte moissonné depuis la source Math-Net.Ru

Voir la notice de l'article

In the article we describe principles of pulse implementation of multilayer neural networks using biologically plausible neurons. It is shown that the multilayer perceptron can be modeled with a neural network composed of pulse neurons using impulse information coding.
Keywords: Impulse coding of information, asymptotic analysis, McCulloch–Pits neuron
Mots-clés : multilayer perceptron. 
@article{MAIS_2011_18_2_a4,
     author = {O. A. Dunaeva},
     title = {Principles of constructing layered neural networks based on pulse neurons},
     journal = {Modelirovanie i analiz informacionnyh sistem},
     pages = {65--76},
     year = {2011},
     volume = {18},
     number = {2},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/MAIS_2011_18_2_a4/}
}
TY  - JOUR
AU  - O. A. Dunaeva
TI  - Principles of constructing layered neural networks based on pulse neurons
JO  - Modelirovanie i analiz informacionnyh sistem
PY  - 2011
SP  - 65
EP  - 76
VL  - 18
IS  - 2
UR  - http://geodesic.mathdoc.fr/item/MAIS_2011_18_2_a4/
LA  - ru
ID  - MAIS_2011_18_2_a4
ER  - 
%0 Journal Article
%A O. A. Dunaeva
%T Principles of constructing layered neural networks based on pulse neurons
%J Modelirovanie i analiz informacionnyh sistem
%D 2011
%P 65-76
%V 18
%N 2
%U http://geodesic.mathdoc.fr/item/MAIS_2011_18_2_a4/
%G ru
%F MAIS_2011_18_2_a4
O. A. Dunaeva. Principles of constructing layered neural networks based on pulse neurons. Modelirovanie i analiz informacionnyh sistem, Tome 18 (2011) no. 2, pp. 65-76. http://geodesic.mathdoc.fr/item/MAIS_2011_18_2_a4/

[1] W. Gerstner, “What's different with spiking neurons?”, Plausible Neural Networks for Biological Modelling, eds. Henk Mastebroek and Hans Vos, Kluwer Academic Publishers, 2001, 23–48 | Zbl

[2] W. Maass, “Fast sigmoidal networks via spiking neurons”, Neural Computation, 9 (1997), 279–304 | DOI | Zbl

[3] W. Maass, T. Natschläger, “Networks of spiking neurons can emulate arbitrary Hopfield nets in temporal coding”, Network: Computation in Neural Systems, 9:4 (1997), 355–372 | DOI

[4] V. V. Maiorov, I. Yu. Myshkin, “Matematicheskoe modelirovanie neironnoi seti na osnove uravnenii s zapazdyvaniem”, Matematicheskoe modelirovanie, 2:11 (1990), 64–76 | MR

[5] S. A. Kaschenko, V. V. Maiorov, “Model adaptatsii koltsevykh neironnykh ansamblei”, Radiotekhnika i Elektronika, 43:11 (1998), 1–7

[6] S. A. Kaschenko, V. V. Maiorov, Modeli volnovoi pamyati, LIBROKOM, M., 2009, 288 pp.

[7] V. V. Maiorov, M. L. Myachin, I. V. Paramonov, “Popravka k periodu resheniya uravneniya, modeliruyuschego dinamiku membrannogo potentsiala neirona”, Modelirovanie i analiz informatsionnykh sistem, 15:2 (2008), 61–66

[8] O. A. Dunaeva, “Utochnenie otsenki latentnogo perioda dlya neironov s sinapticheskim vzaimodeistviem”, Modelirovanie i analiz informatsionnykh sistem, 16:4 (2009), 46–55

[9] F. Uossermen, Neirokompyuternaya tekhnika: Teoriya i praktika, Mir, M., 1992, 184 pp.