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Complex Networks

Complex Networks
Principles, Methods and Applications

  • Publication planned for: September 2017
  • availability: Not yet published - available from September 2017
  • format: Hardback
  • isbn: 9781107103184


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About the Authors
  • 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 the 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.

    • The first textbook integrating all aspects of network science, from fundamental principles to mathematical analysis and computational modelling
    • Provides a comprehensive selection of data sets of social, biological and technological complex networks
    • Includes detailed descriptions of computer algorithms for network analysis and modelling with corresponding implementations in C language freely available online
    • Presents the history of network science alongside the corresponding concepts and mathematical tools, by combining theory with the real-world applications that have inspired network models and algorithms
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    Product details

    • Publication planned for: September 2017
    • format: Hardback
    • isbn: 9781107103184
    • dimensions: 246 x 189 mm
    • contains: 220 b/w illus. 25 tables 58 exercises
    • availability: Not yet published - available from September 2017
  • Table of Contents

    1. Graphs and graph theory
    2. Centrality measures
    3. Random graphs
    4. Small-world networks
    5. Generalised random graphs
    6. Models of growing graphs
    7. Degree correlations
    8. Cycles and motifs
    9. Community structure
    10. Weighted networks
    Author index

  • Authors

    Vito Latora, Queen Mary University of London
    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, Queen Mary University of London
    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, Università degli Studi di Catania, Italy
    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.

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