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Complex Networks - Vito Latora, Vincenzo Nicosia, Giovanni Russo

Complex Networks

Principles, Methods and Applications
Buch | Hardcover
594 Seiten
2017
Cambridge University Press (Verlag)
978-1-107-10318-4 (ISBN)
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Including real-world data sets and ready-to-use software tools, this book encourages hands-on experimentation with complex network data. Students are guided through varying levels of complexity to gain a deep understanding of the basics and applications of network theory, making this an ideal university-level textbook for students across the scientific disciplines.
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.

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.

Preface; Introduction; 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; Appendix; References; Author index; Index.

Erscheinungsdatum
Zusatzinfo Worked examples or Exercises; 25 Tables, black and white; 87 Halftones, black and white; 133 Line drawings, black and white
Verlagsort Cambridge
Sprache englisch
Maße 194 x 253 mm
Gewicht 1410 g
Themenwelt Mathematik / Informatik Informatik Netzwerke
Mathematik / Informatik Mathematik Analysis
Mathematik / Informatik Mathematik Angewandte Mathematik
Naturwissenschaften Physik / Astronomie Allgemeines / Lexika
Naturwissenschaften Physik / Astronomie Thermodynamik
ISBN-10 1-107-10318-5 / 1107103185
ISBN-13 978-1-107-10318-4 / 9781107103184
Zustand Neuware
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