Please use this identifier to cite or link to this item:
Title: Network extreme eigenvalue: From mutimodal to scale-free networks
Authors: Chung, N.N.
Chew, L.Y.
Lai, C.H. 
Issue Date: 3-Jan-2012
Source: Chung, N.N., Chew, L.Y., Lai, C.H. (2012-01-03). Network extreme eigenvalue: From mutimodal to scale-free networks. Chaos 22 (1) : -. ScholarBank@NUS Repository.
Abstract: The extreme eigenvalues of adjacency matrices are important indicators on the influence of topological structures to the collective dynamical behavior of complex networks. Recent findings on the ensemble averageability of the extreme eigenvalue have further authenticated its applicability to the study of network dynamics. However, the ensemble average of extreme eigenvalue has only been solved analytically up to the second order correction. Here, we determine the ensemble average of the extreme eigenvalue and characterize its deviation across the ensemble through the discrete form of random scale-free network. Remarkably, the analytical approximation derived from the discrete form shows significant improvement over previous results, which implies a more accurate prediction of the epidemic threshold. In addition, we show that bimodal networks, which are more robust against both random and targeted removal of nodes, are more vulnerable to the spreading of diseases. © 2012 American Institute of Physics.
Source Title: Chaos
ISSN: 10541500
DOI: 10.1063/1.3697990
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.


checked on Feb 27, 2018


checked on Feb 19, 2018

Page view(s)

checked on Mar 12, 2018

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.