Linked Life Data

20481791

Source:http://linkedlifedata.com/resource/pubmed/id/20481791

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4 Pt 2
pubmed:dateCreated
2010-5-20
pubmed:abstractText
Determining the effect of structural perturbations on the eigenvalue spectra of networks is an important problem because the spectra characterize not only their topological structures, but also their dynamical behavior, such as synchronization and cascading processes on networks. Here we develop a theory for estimating the change of the largest eigenvalue of the adjacency matrix or the extreme eigenvalues of the graph Laplacian when small but arbitrary set of links are added or removed from the network. We demonstrate the effectiveness of our approximation schemes using both real and artificial networks, showing in particular that we can accurately obtain the spectral ranking of small subgraphs. We also propose a local iterative scheme which computes the relative ranking of a subgraph using only the connectivity information of its neighbors within a few links. Our results may not only contribute to our theoretical understanding of dynamical processes on networks, but also lead to practical applications in ranking subgraphs of real complex networks.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Apr
pubmed:issn
1550-2376
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
81
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
046112
pubmed:meshHeading
pubmed:year
2010
pubmed:articleTitle
Approximating spectral impact of structural perturbations in large networks.
pubmed:affiliation
Department of Mechanical & Aeronautical Engineering, Clarkson University, Potsdam, New York 13699-5725, USA. amilanes@cern.ch
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, Non-P.H.S., Research Support, Non-U.S. Gov't