Approximating the largest eigenvalue of network adjacency matrices
Disordered Systems and Neural Networks
2009-11-13 v1
Abstract
The largest eigenvalue of the adjacency matrix of a network plays an important role in several network processes (e.g., synchronization of oscillators, percolation on directed networks, linear stability of equilibria of network coupled systems, etc.). In this paper we develop approximations to the largest eigenvalue of adjacency matrices and discuss the relationships between these approximations. Numerical experiments on simulated networks are used to test our results.
Cite
@article{arxiv.0705.4503,
title = {Approximating the largest eigenvalue of network adjacency matrices},
author = {Juan G. Restrepo and Edward Ott and Brian R. Hunt},
journal= {arXiv preprint arXiv:0705.4503},
year = {2009}
}