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Towards an Information Theory of Complex Networks : Statistical Methods and Applications by Matthias Dehmer, Frank Emmert-Streib, Alexander Mehler is a nonfiction available to read on EtoBox.

What is Towards an Information Theory of Complex Networks : Statistical Methods and Applications about?

For over a decade, complex networks have steadily grown as an important tool across a broad array of academic disciplines, with applications ranging from physics to social media. A tightly organized collection of carefully-selected papers on the subject, Towards an Information Theory of Complex Networks: Statistical Methods and Applications presents theoretical and practical results about information-theoretic and statistical models of complex networks in the natural sciences and humanities. The book's major goal is to advocate and promote a combination of graph-theoretic, information-theoretic, and statistical methods as a way to better understand and characterize real-world networks. This volume is the first to present a self-contained, comprehensive overview of information-theoretic models of complex networks with an emphasis on applications. As such, it marks a first step toward establishing advanced statistical information theory as a unified theoretical basis of complex networks for all scientific disciplines and can serve as a valuable resource for a diverse audience of advanced students and professional scientists. While it is primarily intended as a reference for research,

Who reads Towards an Information Theory of Complex Networks : Statistical Methods and Applications?

Author

Matthias Dehmer, Frank Emmert-Streib, Alexander Mehler

Publisher

Birkhäuser Boston

Published

2011

Language

EN

ISBN

9780817649036

Category

nonfiction

Subjects

Computer Science, Engineering, Mathematics