Masayuki Murata – författare
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3 produkter
3 produkter
Biologically Inspired Approaches to Advanced Information Technology
First International Workshop, BioADIT 2004, Lausanne, Switzerland, January 29-30, 2004. Revised Selected Papers
Häftad, Engelska, 2004
557 kr
Skickas inom 10-15 vardagar
This book constitutes the thoroughly refereed post-proceedings of the First International Workshop on Biologically Inspired Approaches to Advanced Information Technology, BioADIT 2004, held in Lausanne, Switzerland in January 2004.The 36 full papers presented together with an introductory overview have gone through two rounds of reviewing and revision; they were selected and are arranged in a way ensuring systematic coverage of important bio-inspired approaches in computing. The papers are organized in sections on biosystems for IT evolution, bio-inspired software systems, hardware systems, robotics, bio-inspired distributed and parallel processing, bio-inspired networking, image processing, and other topics.
Fluctuation-Induced Network Control and Learning
Applying the Yuragi Principle of Brain and Biological Systems
Inbunden, Engelska, 2021
1 395 kr
Skickas inom 10-15 vardagar
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.
Fluctuation-Induced Network Control and Learning
Applying the Yuragi Principle of Brain and Biological Systems
Häftad, Engelska, 2022
1 395 kr
Skickas inom 10-15 vardagar
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.