Graph Spectra for Complex Networks

"This 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"--

List of contents

Symbols; 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.

About the author

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.

Summary

This 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.

Product details

• Authors: Piet Van Mieghem, Piet Van Mieghem, Piet (Technische Universiteit Delft Van Mieghem, Van Mieghem Piet
• Publisher: Cambridge University Press ELT
• Languages: English
• Product format: Paperback / Softback
• Released: 30.09.2023
• EAN: 9781009366809
• ISBN: 978-1-0-0936680-9
• No. of pages: 535
• Subjects: Natural sciences, medicine, IT, technology > Mathematics > Basic principles; machine learning, TECHNOLOGY & ENGINEERING / Signals & Signal Processing, SCIENCE / Physics / General, COMPUTERS / Networking / General, MATHEMATICS / Discrete Mathematics, MATHEMATICS / Combinatorics, Discrete Mathematics, Signal Processing, Combinatorics & graph theory, Communications engineering / telecommunications, Statistical physics, Computer networking & communications, COMPUTERS / Data Science / Machine Learning, COMPUTERS / Data Science / Neural Networks, Combinatorics and graph theory, Computer networking and communications, Neural networks and fuzzy systems, Neural networks & fuzzy systems