Link-based formalism for time evolution of adaptive networks

Network topology and nodal dynamics are two fundamental stones of adaptive networks. Detailed and accurate knowledge of these two ingredients is crucial for understanding the evolution and mechanism of adaptive networks. In this paper, by adopting the framework of the adaptive SIS model proposed by...

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Main Authors: Zhou, Jie, Xiao, Gaoxi, Chen, Guanrong
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2014
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Online Access:https://hdl.handle.net/10356/101847
http://hdl.handle.net/10220/18770
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1018472020-03-07T14:00:35Z Link-based formalism for time evolution of adaptive networks Zhou, Jie Xiao, Gaoxi Chen, Guanrong School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering Network topology and nodal dynamics are two fundamental stones of adaptive networks. Detailed and accurate knowledge of these two ingredients is crucial for understanding the evolution and mechanism of adaptive networks. In this paper, by adopting the framework of the adaptive SIS model proposed by Gross et al. [Phys. Rev. Lett. 96, 208701 (2006)] and carefully utilizing the information of degree correlation of the network, we propose a link-based formalism for describing the system dynamics with high accuracy and subtle details. Several specific degree correlation measures are introduced to reveal the coevolution of network topology and system dynamics. MOE (Min. of Education, S’pore) Published version 2014-02-06T05:33:49Z 2019-12-06T20:45:34Z 2014-02-06T05:33:49Z 2019-12-06T20:45:34Z 2013 2013 Journal Article Zhou, J., Xiao, G., & Chen, G. (2013). Link-based formalism for time evolution of adaptive networks. Physical Review E, 88(3), 032808-. https://hdl.handle.net/10356/101847 http://hdl.handle.net/10220/18770 10.1103/PhysRevE.88.032808 en Physical review E © 2013 American Physical Society. This paper was published in Physical Review E - Statistical, Nonlinear, and Soft Matter Physics and is made available as an electronic reprint (preprint) with permission of American Physical Society. The paper can be found at the following official DOI: [http://dx.doi.org/10.1103/PhysRevE.88.032808].  One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law. application/pdf
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering
spellingShingle DRNTU::Engineering::Electrical and electronic engineering
Zhou, Jie
Xiao, Gaoxi
Chen, Guanrong
Link-based formalism for time evolution of adaptive networks
description Network topology and nodal dynamics are two fundamental stones of adaptive networks. Detailed and accurate knowledge of these two ingredients is crucial for understanding the evolution and mechanism of adaptive networks. In this paper, by adopting the framework of the adaptive SIS model proposed by Gross et al. [Phys. Rev. Lett. 96, 208701 (2006)] and carefully utilizing the information of degree correlation of the network, we propose a link-based formalism for describing the system dynamics with high accuracy and subtle details. Several specific degree correlation measures are introduced to reveal the coevolution of network topology and system dynamics.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Zhou, Jie
Xiao, Gaoxi
Chen, Guanrong
format Article
author Zhou, Jie
Xiao, Gaoxi
Chen, Guanrong
author_sort Zhou, Jie
title Link-based formalism for time evolution of adaptive networks
title_short Link-based formalism for time evolution of adaptive networks
title_full Link-based formalism for time evolution of adaptive networks
title_fullStr Link-based formalism for time evolution of adaptive networks
title_full_unstemmed Link-based formalism for time evolution of adaptive networks
title_sort link-based formalism for time evolution of adaptive networks
publishDate 2014
url https://hdl.handle.net/10356/101847
http://hdl.handle.net/10220/18770
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