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Complex networks: Structure and dynamics

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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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Pinning synchronization of hybrid-coupled directed delayed dynamical network via intermittent control

TL;DR: It is shown that the controlled synchronization state can vary in comparison with the conventional synchronized solution, and the degree of the node and the inner delayed coupling matrix play important roles in thecontrolled synchronization state.
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Network-based recommendation algorithms: A review

TL;DR: A broad range of network-based recommendation algorithms are reviewed and for the first time their performance on three distinct real datasets is compared.
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Influence of wiring cost on the large-scale architecture of human cortical connectivity.

TL;DR: This work performs a comparative analysis of a connectivity map of the cortical connectome both on high- and low-resolutions utilising three different types of surrogate networks: spatially unconstrained (‘random’, connection length preserving (’spatial’), and connection length optimised (�‘reduced’) surrogates).
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Synchronization of weighted networks and complex synchronized regions

TL;DR: In this paper, a matrix stability problem with respect to a complex parameter is investigated, which gives rise to several types of complex synchronized regions, including bounded, unbounded, disconnected, and empty regions.
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Random Walks, Markov Processes and the Multiscale Modular Organization of Complex Networks

TL;DR: This dynamic framework creates a systematic link between different stochastic dynamics and their corresponding notions of optimal communities under distinct (node and edge) centralities and shows that the Markov Stability can be computed efficiently to find multi-scale community structure in large networks.
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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.
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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.