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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.
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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.

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MuxViz: A Tool for Multilayer Analysis and Visualization of Networks

TL;DR: muxViz as discussed by the authors is a collection of algorithms for the analysis of multilayer networks, which are an important way to represent a large variety of complex systems throughout science and engineering.
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Spectrum of controlling and observing complex networks

TL;DR: It turns out that the extent to which one can exercise control via manipulation of a subset of nodes depends sensitively on the number of nodes perturbed.
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Knowledge transfer in a tourism destination: the effects of a network structure

TL;DR: This conceptual paper examines the nature of networks and how their analysis can shed light upon the processes of knowledge sharing in destinations as they strive to innovate, and shows how epidemic diffusion models can act as analogies for knowledge communication and transfer within a destination network.
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Characterizing the Community Structure of Complex Networks

TL;DR: A systematic empirical analysis of the statistical properties of communities in large information, communication, technological, biological, and social networks finds that the mesoscopic organization of networks of the same category is remarkably similar.
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Recurrence-based time series analysis by means of complex network methods

TL;DR: In this article, the potentials and limitations of the individual methods are discussed and illustrated for paradigmatic examples of dynamical systems as well as for real-world time series, with a special emphasis on methods founded on recurrence plots.
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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
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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.