Graph Spectra for Complex Networks

Author:   Piet van Mieghem (Technische Universiteit Delft, The Netherlands)
Publisher:   Cambridge University Press
ISBN:  

9780511921681


Publication Date:   01 March 2011
Format:   Undefined
Availability:   In stock   Availability explained
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Graph Spectra for Complex Networks


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Overview

Analyzing the behavior of complex networks is an important element in the design of new man-made structures such as communication systems and biologically engineered molecules. Because any complex network can be represented by a graph, and therefore in turn by a matrix, graph theory has become a powerful tool in the investigation of network performance. This self-contained 2010 book provides a concise introduction to the theory of graph spectra and its applications to the study of complex networks. Covering a range of types of graphs and topics important to the analysis of complex systems, this guide provides the mathematical foundation needed to understand and apply spectral insight to real-world systems. In particular, the general properties of both the adjacency and Laplacian spectrum of graphs are derived and applied to complex networks. An ideal resource for researchers and students in communications networking as well as in physics and mathematics.

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Author:   Piet van Mieghem (Technische Universiteit Delft, The Netherlands)
Publisher:   Cambridge University Press
Imprint:   Cambridge University Press (Virtual Publishing)
ISBN:  

9780511921681


ISBN 10:   0511921683
Publication Date:   01 March 2011
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Undefined
Publisher's Status:   Active
Availability:   In stock   Availability explained
We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately.

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Piet Van Mieghem is a Professor at the Delft University of Technology with a chair in telecommunication networks, and chairman of the Network Architectures and Services (NAS) section. His main research interests lie in the modeling and analysis of complex networks (such as biological, brain, social, infrastructural, etc. networks) and in new Internet-like architectures and algorithms for future communications networks.

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