Fluctuation-Induced Network Control and Learning
Language: English
Published by Springer, Springer Nature Singapore Mär 2021, 2021
- Hardcover
- New
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000
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This item is printed on demand - Print on Demand Titel. Neuware -From theory to application, this book presents research on biologically and brain-inspired networking and machine learning based on Yuragi, which is the Japanese term describing the noise or fluctuations that are inherently used to control the dynamics of a system. The Yuragi mechanism can be found in various biological contexts, such as in gene expression dynamics, molecular motors in muscles, or the visual recognition process in the brain. Unlike conventional network protocols that are usually designed to operate under controlled conditions with a predefined set of rules, the probabilistic behavior of Yuragi-based control permits the system to adapt to unknown situations in a distributed and self-organized manner leading to a higher scalability and robustness.The book consists of two parts. Part 1 provides in four chapters an introduction to the biological background of the Yuragi concept as well as how these are applied to networking problems. Part 2 provides additional contributions that extend the original Yuragi concept to a Bayesian attractor model from human perceptual decision making. In the six chapters of the second part, applications to various fields in information network control and artificial intelligence are presented, ranging from virtual network reconfigurations, a software-defined Internet of Things, and low-power wide-area networks.This book will benefit those working in the fields of information networks, distributed systems, and machine learning who seek new design mechanisms for controlling large-scale dynamically changing systems.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 248 pp. Englisch.…
Seller Inventory # 9789813349759
- Title
- Fluctuation-Induced Network Control and Learning
- Author
- Masayuki Murata
- Publisher
- Springer, Springer Nature Singapore Mär 2021
- Publication year
- 2021
- Condition
- Neu
- Binding
- Buch
- Language
- English
- ISBN 10
- 9813349751
- ISBN 13
- 9789813349759
- Item weight
- 541 grams
- Dimensions
- 241x160x20 mm
The book consists of two parts. Part 1 provides in four chapters an introduction to the biological background of the Yuragi concept as well as how these are applied to networking problems. Part 2 provides additional contributions that extend the original Yuragi concept to a Bayesian attractor model from human perceptual decision making. In the six chapters of the second part, applications to various fields in information network control and artificial intelligence are presented, ranging from virtual network reconfigurations, a software-defined Internet of Things, and low-power wide-area networks.
This book will benefit those working in the fields of information networks, distributed systems, and machine learning who seek new design mechanisms for controlling large-scale dynamically changing systems."Synopsis" may belong to another edition of this title.
About the Author
Kenji Leibnitz received his M.Sc. and Ph.D.degrees in information science from the University of Würzburg, Germany, in 2003. In 2004, he joined the research group of Prof. Murata at Osaka University, where he became a specially appointed associate professor in 2006. In 2010, he moved to the National Institute of Information and Communications Technology (NICT) as a senior researcher, and since 2013 he has been a principal investigator at the Center for Information and Neural Networks (CiNet) of NICT and Osaka University. His research interests include modeling and performance analysis of communication networks, especially biologically and brain-inspired mechanisms for self-organization in future networks.
"About the title" may belong to another edition of this title.
buchversandmimpf2000
Emtmannsberg, BAYE, Germany
AbeBooks seller since January 23, 2017
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