Complex Networks: Principles, Methods and Applications 1st Edition

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ISBN 10: 1107103185 / ISBN 13: 9781107103184

Edité par Cambridge University Press, 2017

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Détails bibliographiques

• Titre: Complex Networks: Principles, Methods and Applications 1st Edition
• Éditeur: Cambridge University Press
• Date de parution: 2017
• Langue: anglais
• ISBN à 10 chiffres: 1107103185
• ISBN à 13 chiffres: 9781107103184
• Reliure: Couverture rigide
• État de l'article: Brand New

A propos de ce titre

Synopsis

Networks constitute the backbone of complex systems, from the human brain to computer communications, transport infrastructures to online social systems and metabolic reactions to financial markets. Characterising their structure improves our understanding of the physical, biological, economic and social phenomena that shape our world. Rigorous and thorough, this textbook presents a detailed overview of the new theory and methods of network science. Covering algorithms for graph exploration, node ranking and network generation, among others, the book allows students to experiment with network models and real-world data sets, providing them with a deep understanding of the basics of network theory and its practical applications. Systems of growing complexity are examined in detail, challenging students to increase their level of skill. An engaging presentation of the important principles of network science makes this the perfect reference for researchers and undergraduate and graduate students in physics, mathematics, engineering, biology, neuroscience and the social sciences.

À propos des auteurs

Vito Latora is Professor of Applied Mathematics and Chair of Complex Systems at Queen Mary University of London. Noted for his research in statistical physics and in complex networks, his current interests include time-varying and multiplex networks, and their applications to socio-economic systems and to the human brain.

Vincenzo Nicosia is a Lecturer in Networks and Data Analysis at the School of Mathematical Sciences at Queen Mary University of London. His research spans several aspects of network structure and dynamics, and his recent interests include multi-layer networks and their applications to big data modelling.

Giovanni Russo is Professor of Numerical Analysis in the Department of Mathematics and Computer Science at the Università degli Studi di Catania, Italy, focusing on numerical methods for partial differential equations, with particular application to hyperbolic and kinetic problems.