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Handbook of Large-Scale Random Networks

99,99 €

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

30.11.2011

Abbildungen

600 p.

Herausgeber

Bela Bollobas + weitere

Verlag

Springer Berlin

Seitenzahl

600

Maße (L/B/H)

24,2/17/2,9 cm

Gewicht

913 g

Auflage

2009

Sprache

Englisch

ISBN

978-3-642-24229-8

Beschreibung

Rezension

From the reviews:

“It is a collection of papers on advances in the field of large-scale networks … . The material presented here is based on a workshop organized in Budapest in 2006. … An ideal reader of the book may be a mathematician … .” (Miklós Bóna, The Mathematical Association of America, February, 2010)

“The volume is an outcome of a U.S.-Hungarian workshop on complex networks held at the Rényi Istitute in Budapest in 2006. … I quite enjoyed reading the book. The choice of topics and presentations is illustrative of the type of work taking place in this area … . are likely to be useful to the theoretical computer scientist interested in random structures and algorithms, but most of the chapters were reasonably interesting to me.” (Gabriel Istrate, SIGACT News, April, 2012)

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

30.11.2011

Abbildungen

600 p.

Herausgeber

Verlag

Springer Berlin

Seitenzahl

600

Maße (L/B/H)

24,2/17/2,9 cm

Gewicht

913 g

Auflage

2009

Sprache

Englisch

ISBN

978-3-642-24229-8

Herstelleradresse

Springer-Verlag GmbH
Tiergartenstr. 17
69121 Heidelberg
DE

Email: ProductSafety@springernature.com

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  • Produktbild: Handbook of Large-Scale Random Networks
  • Produktbild: Handbook of Large-Scale Random Networks
  • Random Graphs and Branching Processes.- Percolation, Connectivity, Coverage and Colouring of Random Geometric Graphs.- Scaling Properties of Complex Networks and Spanning Trees.- Random Tree Growth with Branching Processes — A Survey.- Reaction-diffusion Processes in Scale-free Networks.- Toward Understanding the Structure and Function of Cellular Interaction Networks.- Scale-Free Cortical Planar Networks.- Reconstructing Cortical Networks: Case of Directed Graphs with High Level of Reciprocity.- k-Clique Percolation and Clustering.- The Inverse Problem of Evolving Networks — with Application to Social Nets.- Learning and Representation: From Compressive Sampling to the ‘Symbol Learning Problem’.- Telephone Call Network Data Mining: A Survey with Experiments.