scispace - formally typeset
Open AccessJournal ArticleDOI

Complex networks: Structure and dynamics

TLDR
The major concepts and results recently achieved in the study of the structure and dynamics of complex networks are reviewed, and the relevant applications of these ideas in many different disciplines are summarized, ranging from nonlinear science to biology, from statistical mechanics to medicine and engineering.
About
This article is published in Physics Reports.The article was published on 2006-02-01 and is currently open access. It has received 9441 citations till now. The article focuses on the topics: Network dynamics & Complex network.

read more

Figures
Citations
More filters
Journal ArticleDOI

Interacting Epidemics and Coinfection on Contact Networks

TL;DR: A mathematical model of two diseases spreading through a single population, where infection with one disease is dependent on prior infection with the other, is considered, which is used to demonstrate how diseases can be controlled not only by reducing the rate of their spread, but also by reduced the spread of other infections upon which they depend.
Journal ArticleDOI

Robust Stabilization of Complex Switched Networks With Parametric Uncertainties and Delays Via Impulsive Control

TL;DR: In this paper, a general complex switched network (CSN) model is presented and sufficient robust stabilization conditions are proposed for CSNs via impulsive control, based on the Lyapunov stability theory.
Journal ArticleDOI

Master stability functions for complete, intralayer, and interlayer synchronization in multiplex networks of coupled Rössler oscillators.

TL;DR: It is shown how the master stability function, a celebrated framework for analyzing synchronization on a single network, can be extended to certain classes of multiplex networks with different intralayer and interlayer coupling functions.
Journal ArticleDOI

Emergence of Modular Structure in a Large-Scale Brain Network with Interactions between Dynamics and Connectivity.

TL;DR: A network of 32 or 64 connected neural masses was used to demonstrate how an interaction between dynamics and connectivity might explain the emergence of complex network features, in particular modularity, and gives a possible scenario to explain how modularity can arise in developing brain networks.
Journal ArticleDOI

From brain to earth and climate systems: Small-world interaction networks or not?

TL;DR: In this article, the authors consider the small-world topology of interaction networks derived from the dynamics of spatially extended systems that are investigated in diverse scientific fields such as neurosciences, geophysics, or meteorology.
References
More filters
Journal ArticleDOI

Optimization by Simulated Annealing

TL;DR: There is a deep and useful connection between statistical mechanics and multivariate or combinatorial optimization (finding the minimum of a given function depending on many parameters), and a detailed analogy with annealing in solids provides a framework for optimization of very large and complex systems.
Book

Computers and Intractability: A Guide to the Theory of NP-Completeness

TL;DR: The second edition of a quarterly column as discussed by the authors provides a continuing update to the list of problems (NP-complete and harder) presented by M. R. Garey and myself in our book "Computers and Intractability: A Guide to the Theory of NP-Completeness,” W. H. Freeman & Co., San Francisco, 1979.
Journal ArticleDOI

Collective dynamics of small-world networks

TL;DR: Simple models of networks that can be tuned through this middle ground: regular networks ‘rewired’ to introduce increasing amounts of disorder are explored, finding that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs.
Book

Matrix computations

Gene H. Golub
Frequently Asked Questions (1)
Q1. What are the contributions in "Complex networks: structure and dynamics" ?

The authors review the major concepts and results recently achieved in the study of the structure and dynamics of complex networks, and summarize the relevant applications of these ideas in many different disciplines, ranging from nonlinear science to biology, from statistical mechanics to medicine and engineering.