Könyv Complex Networks Kayhan Erciyes

Complex Networks

Szerző: Kayhan Erciyes
Nyelv: Angol
Kötés: Puha kötésű
Elérhetőség: 50 % esély
Keressük az egész világon
25 215 Ft
Network science is a rapidly emerging field of study that encompasses mathematics, computer science,...

Információk a könyvről

Szerző
Nyelv
Angol
Kötés
Könyv - Puha kötésű
Kiadva
2017
oldal
320
EAN
9781138033894
ISBN
9781138033894
Enbook ID
14235746
Súly
590
Méretek
156 x 234

Teljes leírás

Network science is a rapidly emerging field of study that encompasses mathematics, computer science, physics, and engineering. A key issue in the study of complex networks is to understand the collective behavior of the various elements of these networks.

Although the results from graph theory have proven to be powerful in investigating the structures of complex networks, few books focus on the algorithmic aspects of complex network analysis. Filling this need, Complex Networks: An Algorithmic Perspective supplies the basic theoretical algorithmic and graph theoretic knowledge needed by every researcher and student of complex networks.

This book is about specifying, classifying, designing, and implementing mostly sequential and also parallel and distributed algorithms that can be used to analyze the static properties of complex networks. Providing a focused scope which consists of graph theory and algorithms for complex networks, the book identifies and describes a repertoire of algorithms that may be useful for any complex network.

  • Provides the basic background in terms of graph theory
  • Supplies a survey of the key algorithms for the analysis of complex networks
  • Presents case studies of complex networks that illustrate the implementation of algorithms in real-world networks, including protein interaction networks, social networks, and computer networks

Requiring only a basic discrete mathematics and algorithms background, the book supplies guidance that is accessible to beginning researchers and students with little background in complex networks. To help beginners in the field, most of the algorithms are provided in ready-to-be-executed form.

While not a primary textbook, the author has included pedagogical features such as learning objectives, end-of-chapter summaries, and review questions

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