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Graph Spectra for Complex Networks by Piet Van Mieghem (2023, Trade Paperback)

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Graph Spectra for Complex Networks, Paperback by Van Mieghem, Piet, ISBN 1009366807, ISBN-13 9781009366809, Brand New, Free shipping in the US

About this product

Product Identifiers

PublisherCambridge University Press

ISBN-101009366807

ISBN-139781009366809

eBay Product ID (ePID)22061242188

Product Key Features

Number of Pages535 Pages

LanguageEnglish

Publication NameGraph Spectra for Complex Networks

Publication Year2023

SubjectGeneral

TypeTextbook

Subject AreaMathematics, Computers

AuthorPiet Van Mieghem

FormatTrade Paperback

Dimensions

Item Height1.2 in

Item Length9.5 in

Item Width6.7 in

Additional Product Features

Edition Number2

LCCN2023-023240

Dewey Edition23/eng/20231002

Reviews'This book provides a comprehensive background in the area, especially for researchers and graduate students ... Highly recommended.' J. T. Saccoman, CHOICE

IllustratedYes

Dewey Decimal511/.5

Table Of ContentSymbols; 1. Introduction; Part I. Spectra of Graphs: 2. Algebraic graph theory; 3. Eigenvalues of the adjacency matrix; 4. Eigenvalues of the Laplacian Q; 5. Effective resistance matrix; 6. Spectra of special types of graphs; 7. Density function of the eigenvalues; 8. Spectra of complex networks; Part II. Eigensystem: 9. Topics in linear algebra; 10. Eigensystem of a matrix; Part III. Polynomials: 11. Polynomials with real coefficients; 12. Orthogonal polynomials; References; Index.

SynopsisThis concise and self-contained introduction builds up the spectral theory of graphs from scratch, including linear algebra and the theory of polynomials. Covering several types of graphs, it provides the mathematical foundation needed to understand and apply spectral insight to real-world communications systems and complex networks., 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.

LC Classification NumberQA166.V365 2023