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Statistical Analysis of Graph Structures in Random Variable Networks Paperback / softback
by V. A. Kalyagin, A. P. Koldanov, P. A. Koldanov, P. M. Pardalos
Part of the SpringerBriefs in Optimization series
Paperback / softback
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Description
This book studies complex systems with elements represented by random variables.
Its main goal is to study and compare uncertainty of algorithms of network structure identification with applications to market network analysis.
For this, a mathematical model of random variable network is introduced, uncertainty of identification procedure is defined through a risk function, random variables networks with different measures of similarity (dependence) are discussed, and general statistical properties of identification algorithms are studied.
The volume also introduces a new class of identification algorithms based on a new measure of similarity and prove its robustness in a large class of distributions, and presents applications to social networks, power transmission grids, telecommunication networks, stock market networks, and brain networks through a theoretical analysis that identifies network structures.
Both researchers and graduate students in computer science, mathematics, and optimization will find the applications and techniques presented useful.
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Available to Order - This title is available to order, with delivery expected within 2 weeks
- Format:Paperback / softback
- Pages:101 pages, 3 Illustrations, color; 6 Illustrations, black and white; VIII, 101 p. 9 illus., 3 illus.
- Publisher:Springer Nature Switzerland AG
- Publication Date:06/12/2020
- Category:
- ISBN:9783030602925
Other Formats
- EPUB from £38.24
Information
-
Available to Order - This title is available to order, with delivery expected within 2 weeks
- Format:Paperback / softback
- Pages:101 pages, 3 Illustrations, color; 6 Illustrations, black and white; VIII, 101 p. 9 illus., 3 illus.
- Publisher:Springer Nature Switzerland AG
- Publication Date:06/12/2020
- Category:
- ISBN:9783030602925