Graph Spectra for Complex Networks

Author:   Piet Van Mieghem (Technische Universiteit Delft, The Netherlands)
Publisher:   Cambridge University Press
Edition:   2nd Revised edition
ISBN:  

9781009366809


Pages:   535
Publication Date:   21 September 2023
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Graph Spectra for Complex Networks


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Overview

This concise and self-contained introduction builds up the spectral theory of graphs from scratch, with linear algebra and the theory of polynomials developed in the later parts. The book focuses on properties and bounds for the eigenvalues of the adjacency, Laplacian and effective resistance matrices of a graph. The goal of the book is to collect spectral properties that may help to understand the behavior or main characteristics of real-world networks. The chapter on spectra of complex networks illustrates how the theory may be applied to deduce insights into real-world networks. The second edition contains new chapters on topics in linear algebra and on the effective resistance matrix, and treats the pseudoinverse of the Laplacian. The latter two matrices and the Laplacian describe linear processes, such as the flow of current, on a graph. The concepts of spectral sparsification and graph neural networks are included.

Full Product Details

Author:   Piet Van Mieghem (Technische Universiteit Delft, The Netherlands)
Publisher:   Cambridge University Press
Imprint:   Cambridge University Press
Edition:   2nd Revised edition
Weight:   0.913kg
ISBN:  

9781009366809


ISBN 10:   1009366807
Pages:   535
Publication Date:   21 September 2023
Audience:   College/higher education ,  Postgraduate, Research & Scholarly
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

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Piet Van Mieghem is Professor at the Delft University of Technology. His research interests lie in network science: the modeling and analysis of complex networks such as infrastructural networks (for example telecommunication, power grids and transportation) as well as biological, brain, social and economic networks.

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