Statistical Mechanics of Complex Networks

Inbunden, Engelska, 2003

534 kr

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Beskrivning

Networks can provide a useful model and graphic image useful for the description of a wide variety of web-like structures in the physical and man-made realms, e.g. protein networks, food webs and the Internet. The contributions gathered in the present volume provide both an introduction to, and an overview of, the multifaceted phenomenology of complex networks. Statistical Mechanics of Complex Networks also provides a state-of-the-art picture of current theoretical methods and approaches.

Produktinformation

Utgivningsdatum:2003-08-08
Mått:155 x 235 x 19 mm
Vikt:547 g
Format:Inbunden
Språk:Engelska
Serie:Lecture Notes in Physics
Antal sidor:206
Upplaga:2003
Förlag:Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
ISBN:9783540403722

Utforska kategorier

Matematik inom Naturvetenskap och teknik

Recensioner i media

"The editors have done a very good job compiling this collection of essays written by leading experts in the field of statistical mechanics of networks. Although a book like this can never be entirely up-to-date, the articles reflect the current state of affairs very well. Most of them are self-contained and define the various terms and quantities carefully before using them. That leads to a certain amount of redundant information and overlap, yet it enables the reader to simply dip in and get a good idea of what the hot topics in complex networks are. I strongly recommend the book to anyone who wants to start her or his own work in complex networks." (Contemporary Physics 2005, 46, page 240-241)

Innehållsförteckning

Rate Equations Approach for Growing Networks.- Directed and Non-Directed Scale-Free Networks.- Mixing Patterns and Community Structure in Networks.- Effect of Accelerated Growth on Networks Dynamics.- Optimization in Complex Networks.- Epidemic Spreading in Complex Networks With Degree Correlations.- Food Web Structure and the Evolution of Complex Networks.- Social Networks: From Sexual Networks to Threatened Networks.- Search and Congestion in Complex Networks.- Membrane Clusters of Ion Channels.