On connected component distribution of random block-hierarchical networks using the automated system $xRandNet$
Proceedings of the Yerevan State University. Physical and mathematical sciences, Tome 52 (2018) no. 1, pp. 34-40.

Voir la notice de l'article provenant de la source Math-Net.Ru

This paper presents the result of a research done using the automated system $xRandNet$, which is designed and implemented for generating and analyzing the main topological properties of some hierarchical models of random networks. The research is on connected component distribution of random block-hierarchical networks, which are quite new objects in the random network theory.
Keywords: random networks, block-hierarchical networks, connected component distribution, automated system.
@article{UZERU_2018_52_1_a5,
     author = {A. G. Kocharyan},
     title = {On connected component distribution of random block-hierarchical networks using the automated system $xRandNet$},
     journal = {Proceedings of the Yerevan State University. Physical and mathematical sciences},
     pages = {34--40},
     publisher = {mathdoc},
     volume = {52},
     number = {1},
     year = {2018},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/UZERU_2018_52_1_a5/}
}
TY  - JOUR
AU  - A. G. Kocharyan
TI  - On connected component distribution of random block-hierarchical networks using the automated system $xRandNet$
JO  - Proceedings of the Yerevan State University. Physical and mathematical sciences
PY  - 2018
SP  - 34
EP  - 40
VL  - 52
IS  - 1
PB  - mathdoc
UR  - http://geodesic.mathdoc.fr/item/UZERU_2018_52_1_a5/
LA  - en
ID  - UZERU_2018_52_1_a5
ER  - 
%0 Journal Article
%A A. G. Kocharyan
%T On connected component distribution of random block-hierarchical networks using the automated system $xRandNet$
%J Proceedings of the Yerevan State University. Physical and mathematical sciences
%D 2018
%P 34-40
%V 52
%N 1
%I mathdoc
%U http://geodesic.mathdoc.fr/item/UZERU_2018_52_1_a5/
%G en
%F UZERU_2018_52_1_a5
A. G. Kocharyan. On connected component distribution of random block-hierarchical networks using the automated system $xRandNet$. Proceedings of the Yerevan State University. Physical and mathematical sciences, Tome 52 (2018) no. 1, pp. 34-40. http://geodesic.mathdoc.fr/item/UZERU_2018_52_1_a5/

[1] R. Albert, A. L. Barabasi, “Statistical Mechanics of Complex Networks”, Rev. Mod. Phys., 74 (2002), 47–97 | DOI | MR

[2] V. A. Avetisov, A. Kh. Bikulov, O. A. Vasilyev et al., “Some Physical Applications of Random Hierarchical Matrices”, JETP, 109:3 (2009), 485–504 | DOI | MR

[3] P. Moretti, M. A. Muñoz, “Griffiths Phases and the Stretching of Criticality in Brain Networks”, Nature Communications, 2013, no. 4, 2521–547

[4] A. G. Kocharyan, “Application xRandNet for Studying the Topological Properties of Random Networks”, Proceedings of the NAS RA and SEUA. Ser. Technical Sciences, 70:4 (2017), 519–529 (in Russian)

[5] S. Avetisyan, A. Harutyunyan, D. Aslanyan et al., “Algorithms for Computation of Statistical Properties of Regular Block-hierarchical Networks”, Proceedings of the 6th Annual Scientific Conference (RAU, 2012), 108–121 (in Russian)

[6] S. Avetisyan, M. Samvelyan, M. Karapetyan, “Random Irregular Block-Hierarchical Networks: Algorithms for Computation of Main Properties”, Proceedings of the 9th Annual Scientific Conference (RAU, 2015), 48–60 (in Russian)

[7] A. L. Barabasi, Network Science, Cambridge University Press, 2016, 456 pp.