Random Graphs and Networks: A First Course

"Based on the authors' own teaching experience, this text introduces random graphs and networks, covering all the basic features before discussing the growth and structure of real-world networks. It can be used as a textbook for a one-semester course at advanced undergraduate or graduate level"--

Sommario

Conventions/Notation; Part I. Preliminaries: 1. Introduction; 2. Basic tools; Part II. Erdos-Rényi-Gilbert Model: 3. Uniform and binomial random graphs; 4. Evolution; 5. Vertex degrees; 6. Connectivity; 7. Small subgraphs; 8. Large subgraphs; 9. Extreme characteristics; Part III. Modeling Complex Networks: 10. Inhomogeneous graphs; 11. Small world; 12. Network processes; 13. Intersection graphs; 14. Weighted graphs; References; Author index; Main index.

Info autore

Alan Frieze is Professor in the Department of Mathematical Sciences at Carnegie Mellon University. He has authored almost 400 publications in top journals and was a plenary speaker at the 2014 International Congress of Mathematicians.Michał Karoński is Professor Emeritus in the Faculty of Mathematics and Computer Science at Adam Mickiewicz University, where he founded the Discrete Mathematics group. He served as Editor-in-Chief of 'Random Structures and Algorithms' for thirty years.

Dettagli sul prodotto

• Autori: Alan Frieze, Alan (Carnegie Mellon University Frieze, Frieze Alan, Karo&, Michal Karo&324;ski, Michal (Adam Mickiewicz University Karonski, Michał Karoński
• Editore: Cambridge University Press ELT
• Lingue: Inglese
• Formato: Tascabile
• Pubblicazione: 30.04.2023
• EAN: 9781009260305
• ISBN: 978-1-0-0926030-5
• Pagine: 232
• Categorie: Scienze naturali, medicina, informatica, tecnica > Matematica > Teoria delle probabilità, stocastica, statistica matematica; Scienze sociali, diritto, economia > Media, comunicazione > Scienze della comunicazione; COMPUTERS / Computer Science, COMPUTERS / Information Theory, MATHEMATICS / Discrete Mathematics, computer science, Discrete Mathematics, Information theory