UID:
almahu_9948621871902882
Format:
VIII, 101 p. 9 illus., 3 illus. in color.
,
online resource.
Edition:
1st ed. 2020.
ISBN:
9783030602932
Series Statement:
SpringerBriefs in Optimization,
Content:
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.
Note:
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.
In:
Springer Nature eBook
Additional Edition:
Printed edition: ISBN 9783030602925
Additional Edition:
Printed edition: ISBN 9783030602949
Language:
English
DOI:
10.1007/978-3-030-60293-2
URL:
https://doi.org/10.1007/978-3-030-60293-2
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