scispace - formally typeset
Open AccessJournal ArticleDOI

Complex networks: Structure and dynamics

Reads0
Chats0
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

Network analysis of human heartbeat dynamics

TL;DR: In this paper, the authors constructed the complex networks of human heartbeat dynamics and investigated their statistical properties, using the visibility algorithm proposed by Lacasa and co-workers, and showed that the associated networks for the time series of heartbeat interval are always scale-free, high clustering, hierarchy, and assortative mixing.
Journal ArticleDOI

Principles of recovery from traumatic brain injury: Reorganization of functional networks

TL;DR: The results indicate that: 1) the principle of recovery depends on the spectral band, 2) the structure of the functional networks evolves in parallel to brain recovery with correlations with neuropsychological scales, and 3) energetic cost reveals an optimal principle of Recovery.
Journal ArticleDOI

Model Reduction and Clusterization of Large-Scale Bidirectional Networks

TL;DR: Two model reduction methods for large-scale bidirectional networks that fully utilize a network structure transformation implemented as positive tridiagonalization are proposed and a novel model reduction method is proposed that preserves network topology among clusters, i.e., node sets.
Journal ArticleDOI

Model-free information-theoretic approach to infer leadership in pairs of zebrafish.

TL;DR: This work demonstrates an information-theoretic approach to infer leadership from positional data of fish swimming, and focuses on the zebrafish model organism, which is rapidly emerging as a species of choice in preclinical research for its genetic similarity to humans and reduced neurobiological complexity with respect to mammals.
Journal ArticleDOI

Fractality and self-similarity in scale-free networks

TL;DR: In this paper, the authors reviewed and investigated the fractal scaling and self-similar connectivity behavior of scale-free networks in diverse aspects, and showed that the skeleton is a non-causal tree, either critical or supercritical.
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.