Title
Estimating and increasing the structural robustness of a network
Abstract
The capability of a network to cope with threats and survive attacks is referred to as its robustness. This article discusses one kind of robustness, commonly denoted structural robustness, which increases when the spectral radius of the adjacency matrix associated with the network decreases. We discuss computational techniques for identifying edges, whose removal may significantly reduce the spectral radius. Nonsymmetric adjacency matrices are studied with the aid of their pseudospectra. In particular, we consider nonsymmetric adjacency matrices that arise when people seek to avoid being infected by Covid-19 by wearing facial masks of different qualities.
Year
DOI
Venue
2022
10.1002/nla.2418
NUMERICAL LINEAR ALGEBRA WITH APPLICATIONS
Keywords
DocType
Volume
network analysis, Perron vector, pseudospectra, structured perturbation
Journal
29
Issue
ISSN
Citations 
2
1070-5325
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Silvia Noschese100.34
Lothar Reichel245395.02