The availability of large data sets has allowed researchers to uncover complex properties such as large-scale fluctuations and heterogeneities in many networks, leading to the breakdown of standard theoretical frameworks and models. Until recently these systems were considered as haphazard sets of points and connections. Recent advances have generated a vigorous research effort in understanding the effect of complex connectivity patterns on dynamical phenomena. This book presents a comprehensive account of these effects. A vast number of systems, from the brain to ecosystems, power grids and the internet, can be represented as large complex networks. This book will interest graduate students and researchers in many disciplines, from physics and statistical mechanics to mathematical biology and information science. Its modular approach allows readers to readily access the sections of most interest to them, and complicated maths is avoided so the text can be easily followed by non-experts in the subject.
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Alain Barrat is Senior Researcher at the Centre de Physique Théorique (CNRS and Aix-Marseille University, France) and at the Institute for Scientific Interchange in Turin, Italy. His research interests are in the field of out-of-equilibrium statistical mechanics.
Marc Barthélemy is Senior Researcher at the Institute for Theoretical Physics (IPhT) at the Commissariat à l'Énergie Atomique et aux Energies Alternatives (CEA), France. His research interests are in the application of statistical physics to complex systems.
Alessandro Vespignani is Sternberg Distinguished Professor in Physics, Computer Science and Health Science at Northeastern University, USA. He is also Fellow of the Institute for Quantitative Social Sciences at Harvard University and Scientific Director of the Institute for Scientific Interchange Foundation in Italy.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Etat : New. An in-depth account on complex connectivity patterns for graduates and researchers in statistical mechanics, mathematical biology and information science. Num Pages: 366 pages, 98 b/w illus. BIC Classification: PBW; PHS; UT. Category: (UP) Postgraduate, Research & Scholarly. Dimension: 257 x 182 x 22. Weight in Grams: 794. . 2008. 1st Edition. hardcover. . . . . N° de réf. du vendeur V9780521879507
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Hardcover. Etat : new. Hardcover. The availability of large data sets has allowed researchers to uncover complex properties such as large-scale fluctuations and heterogeneities in many networks, leading to the breakdown of standard theoretical frameworks and models. Until recently these systems were considered as haphazard sets of points and connections. Recent advances have generated a vigorous research effort in understanding the effect of complex connectivity patterns on dynamical phenomena. This book presents a comprehensive account of these effects. A vast number of systems, from the brain to ecosystems, power grids and the internet, can be represented as large complex networks. This book will interest graduate students and researchers in many disciplines, from physics and statistical mechanics to mathematical biology and information science. Its modular approach allows readers to readily access the sections of most interest to them, and complicated maths is avoided so the text can be easily followed by non-experts in the subject. An in-depth account on the effect of complex connectivity patterns on dynamical phenomena, this book will interest graduate students and researchers in many disciplines, from physics and statistical mechanics to mathematical biology and information science. Its modular approach allows readers to easily access the sections of most interest to them. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9780521879507
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