Statistical Analysis of Graph Structures in Random Variable Networks

题名:

ISBN:

9783030602932

个人著者:

Kalyagin, V. A. author.

版:

1st ed. 2020.

PRODUCTION_INFO:

Cham : Springer International Publishing : Imprint: Springer, 2020.

物理描述:

VIII, 101 p. 9 illus., 3 illus. in color. online resource.

系列:

SpringerBriefs in Optimization,

内容:

1. Introduction -- 2. Random variable networks. -3. Network Identification Structure Algorithms -- 4. Uncertainty of Network Structure Identification -- 5. Robustness of Network Structure Identification -- 6. Optimality of Network Structure Identification -- 7. Applications to Market Network Analysis -- 8. Conclusion -- 9. References.

摘要:

This book presents new theoretical approaches for statistical network analysis in random variable networks. Robustness and optimality of statistical procedures for various network structures are detailed and analyzed. Applications to social networks, power transmission grids, telecommunication networks, stock market networks, and brain networks are presented through a theoretical analysis which identifies network structures. Graduate students and researchers in computer science, mathematics, and optimization will find the applications and techniques presented useful.

主题词汇:

Mathematical optimization.

Computer engineering.

Computer networks .

Probabilities.

Neural networks (Computer science) .

Optimization.

Computer Engineering and Networks.

Probability Theory.

Mathematical Models of Cognitive Processes and Neural Networks.

附加著者:

Koldanov, A. P.