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Fluctuation-Induced Network Control and Learning - Applying the Yuragi Principle of Brain and Biological Systems (Hardcover, 1st ed. 2021)
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Fluctuation-Induced Network Control and Learning - Applying the Yuragi Principle of Brain and Biological Systems (Hardcover, 1st ed. 2021)
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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.
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