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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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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.
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Statistical Analysis of Graph Structures in Random Variable Networks
Editore:
Springer International Publishing, 2020
ISBN 10: 3030602923
ISBN 13: 9783030602925
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Da: moluna, Greven, Germania
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 mo. Codice articolo 448685570
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Statistical Analysis of Graph Structures in Random Variable Networks
Editore:
Springer International Publishing Dez 2020, 2020
ISBN 10: 3030602923
ISBN 13: 9783030602925
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 112 pp. Englisch. Codice articolo 9783030602925
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Statistical Analysis of Graph Structures in Random Variable Networks
Editore:
Springer International Publishing, 2020
ISBN 10: 3030602923
ISBN 13: 9783030602925
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Da: AHA-BUCH GmbH, Einbeck, Germania
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Codice articolo 9783030602925
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Statistical Analysis of Graph Structures in Random Variable Networks
ISBN 10: 3030602923
ISBN 13: 9783030602925
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
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Taschenbuch. Condizione: Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 112 pp. Englisch. Codice articolo 9783030602925
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Statistical Analysis of Graph Structures in Random Variable Networks
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Statistical Analysis of Graph Structures in Random Variable Networks (SpringerBriefs in Optimization)
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Statistical Analysis of Graph Structures in Random Variable Networks (SpringerBriefs in Optimization)
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Statistical Analysis of Graph Structures in Random Variable Networks
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Statistical Analysis of Graph Structures in Random Variable Networks
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Statistical Analysis of Graph Structures in Random Variable Networks (SpringerBriefs in Optimization)
Da: Books Puddle, New York, NY, U.S.A.
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Condizione: New. 1st ed. 2020 edition NO-PA16APR2015-KAP. Codice articolo 26388716345
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