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Self-Organization of Weighted Networks for Optimal Synchronizability

Research output: Contribution to journalArticle

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Self-Organization of Weighted Networks for Optimal Synchronizability. / Kempton, Louis; Herrmann, Guido; Di Bernardo, Mario.

In: IEEE Transactions on Control of Network Systems, Vol. 5, No. 4, 7993095, 01.12.2018, p. 1541-1550.

Research output: Contribution to journalArticle

Harvard

Kempton, L, Herrmann, G & Di Bernardo, M 2018, 'Self-Organization of Weighted Networks for Optimal Synchronizability', IEEE Transactions on Control of Network Systems, vol. 5, no. 4, 7993095, pp. 1541-1550. https://doi.org/10.1109/TCNS.2014.2301653, https://doi.org/10.1109/TCNS.2017.2732161

APA

Kempton, L., Herrmann, G., & Di Bernardo, M. (2018). Self-Organization of Weighted Networks for Optimal Synchronizability. IEEE Transactions on Control of Network Systems, 5(4), 1541-1550. [7993095]. https://doi.org/10.1109/TCNS.2014.2301653, https://doi.org/10.1109/TCNS.2017.2732161

Vancouver

Kempton L, Herrmann G, Di Bernardo M. Self-Organization of Weighted Networks for Optimal Synchronizability. IEEE Transactions on Control of Network Systems. 2018 Dec 1;5(4):1541-1550. 7993095. https://doi.org/10.1109/TCNS.2014.2301653, https://doi.org/10.1109/TCNS.2017.2732161

Author

Kempton, Louis ; Herrmann, Guido ; Di Bernardo, Mario. / Self-Organization of Weighted Networks for Optimal Synchronizability. In: IEEE Transactions on Control of Network Systems. 2018 ; Vol. 5, No. 4. pp. 1541-1550.

Bibtex

@article{79f1e3f0cc1b47e198ed5396284e7b95,
title = "Self-Organization of Weighted Networks for Optimal Synchronizability",
abstract = "We show that a network can self-organize its existing topology, i.e., by adapting edge weights, in a completely decentralized manner in order to maximize its synchronizability while satisfying local constraints: we look specifically at nonnegativity of edge weights and maximum weighted degree of nodes. A novel multilayer approach is presented, which uses a decentralized strategy through which each node can estimate one of two spectral functions of the graph Laplacian, the algebraic connectivity λ2, or the eigenratio r=λn / λ2. These local estimates are then used to evolve the edge weights so as to maximize λ2, or minimize r, and, hence, achieve globally optimal values for the edge weights for the synchronization of a network of coupled systems.",
keywords = "Complex networks, decentralized control, optimization",
author = "Louis Kempton and Guido Herrmann and {Di Bernardo}, Mario",
year = "2018",
month = "12",
day = "1",
doi = "10.1109/TCNS.2014.2301653",
language = "English",
volume = "5",
pages = "1541--1550",
journal = "IEEE Transactions on Control of Network Systems",
issn = "2325-5870",
publisher = "Institute of Electrical and Electronics Engineers (IEEE)",
number = "4",

}

RIS - suitable for import to EndNote

TY - JOUR

T1 - Self-Organization of Weighted Networks for Optimal Synchronizability

AU - Kempton, Louis

AU - Herrmann, Guido

AU - Di Bernardo, Mario

PY - 2018/12/1

Y1 - 2018/12/1

N2 - We show that a network can self-organize its existing topology, i.e., by adapting edge weights, in a completely decentralized manner in order to maximize its synchronizability while satisfying local constraints: we look specifically at nonnegativity of edge weights and maximum weighted degree of nodes. A novel multilayer approach is presented, which uses a decentralized strategy through which each node can estimate one of two spectral functions of the graph Laplacian, the algebraic connectivity λ2, or the eigenratio r=λn / λ2. These local estimates are then used to evolve the edge weights so as to maximize λ2, or minimize r, and, hence, achieve globally optimal values for the edge weights for the synchronization of a network of coupled systems.

AB - We show that a network can self-organize its existing topology, i.e., by adapting edge weights, in a completely decentralized manner in order to maximize its synchronizability while satisfying local constraints: we look specifically at nonnegativity of edge weights and maximum weighted degree of nodes. A novel multilayer approach is presented, which uses a decentralized strategy through which each node can estimate one of two spectral functions of the graph Laplacian, the algebraic connectivity λ2, or the eigenratio r=λn / λ2. These local estimates are then used to evolve the edge weights so as to maximize λ2, or minimize r, and, hence, achieve globally optimal values for the edge weights for the synchronization of a network of coupled systems.

KW - Complex networks

KW - decentralized control

KW - optimization

UR - http://www.scopus.com/inward/record.url?scp=85028946413&partnerID=8YFLogxK

U2 - 10.1109/TCNS.2014.2301653

DO - 10.1109/TCNS.2014.2301653

M3 - Article

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EP - 1550

JO - IEEE Transactions on Control of Network Systems

JF - IEEE Transactions on Control of Network Systems

SN - 2325-5870

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ER -