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Fluctuation-Induced Network Control and Learning

Overview of attention for book
Cover of 'Fluctuation-Induced Network Control and Learning'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction to Yuragi Theory and Yuragi Control
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    Chapter 2 Functional Roles of Yuragi in Biosystems
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    Chapter 3 Next-Generation Bio- and Brain-Inspired Networking
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    Chapter 4 Yuragi-Based Virtual Network Control
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    Chapter 5 Introduction to Yuragi Learning
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    Chapter 6 Fast/Slow-Pathway Bayesian Attractor Model for IoT Networks Based on Software-Defined Networking with Virtual Network Slicing
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    Chapter 7 Application to IoT Network Control: Predictive Network Control Based on Real-World Information
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    Chapter 8 Another Prediction Method and Application to Low-Power Wide-Area Networks
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    Chapter 9 Artificial Intelligence Platform for Yuragi Learning
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    Chapter 10 Bias-Free Yuragi Learning
Attention for Chapter 1: Introduction to Yuragi Theory and Yuragi Control
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Citations

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Chapter title
Introduction to Yuragi Theory and Yuragi Control
Chapter number 1
Book title
Fluctuation-Induced Network Control and Learning
Published by
Springer, Singapore, November 2020
DOI 10.1007/978-981-33-4976-6_1
Book ISBNs
978-9-81-334975-9, 978-9-81-334976-6
Authors

Kenji Leibnitz, Leibnitz, Kenji

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 1 100%
Readers by discipline Count As %
Computer Science 1 100%

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