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Analysis and Control of Coupled Neural Networks with Reaction-Diffusion Terms

  • Book
  • © 2018

Overview

Authors:
  1. Jin-Liang Wang

    1. Tianjin Polytechnic University , Tianjin, China

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  2. Huai-Ning Wu

    1. Beihang University , Beijing, China

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  3. Tingwen Huang

    1. Texas A&M University at Qatar , Doha, Qatar

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  4. Shun-Yan Ren

    1. Tianjin Polytechnic University , Tianjin, China

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  • Takes the reaction-diffusion effect into account in neural networks
  • Proposes new passivity definitions for cases in which the input and output vectors have different dimensions in coupled reaction-diffusion neural networks
  • Helps readers understand the dynamical behaviors of coupled reaction-diffusion neural networks
  • Includes supplementary material: sn.pub/extras

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Table of contents (10 chapters)

  1. Front Matter

    Pages i-xiii
    Download chapter PDF

  2. Introduction

    • Jin-Liang Wang, Huai-Ning Wu, Tingwen Huang, Shun-Yan Ren
    Pages 1-12

  3. Pinning Control Strategies for Synchronization of CRDNNs

    • Jin-Liang Wang, Huai-Ning Wu, Tingwen Huang, Shun-Yan Ren
    Pages 13-38

  4. Pinning Control for Synchronization of CRDNNs with Directed Topologies

    • Jin-Liang Wang, Huai-Ning Wu, Tingwen Huang, Shun-Yan Ren
    Pages 39-61

  5. Impulsive Control for the Synchronization of CRDNNs

    • Jin-Liang Wang, Huai-Ning Wu, Tingwen Huang, Shun-Yan Ren
    Pages 63-80

  6. Novel Adaptive Strategies for Synchronization of CRDNNs

    • Jin-Liang Wang, Huai-Ning Wu, Tingwen Huang, Shun-Yan Ren
    Pages 81-103

  7. Synchronization and Adaptive Control of CRDNNs with Hybrid Coupling

    • Jin-Liang Wang, Huai-Ning Wu, Tingwen Huang, Shun-Yan Ren
    Pages 105-128

  8. Passivity-Based Synchronization of CRDNNs with Time-Varying Delay

    • Jin-Liang Wang, Huai-Ning Wu, Tingwen Huang, Shun-Yan Ren
    Pages 129-141

  9. Passivity and Synchronization of CRDNNs with Adaptive Coupling

    • Jin-Liang Wang, Huai-Ning Wu, Tingwen Huang, Shun-Yan Ren
    Pages 143-159

  10. Passivity Analysis of CRDNNs with Dirichlet Boundary Conditions

    • Jin-Liang Wang, Huai-Ning Wu, Tingwen Huang, Shun-Yan Ren
    Pages 161-184

  11. Passivity of Directed and Undirected CRDNNs with Adaptive Coupling Weights

    • Jin-Liang Wang, Huai-Ning Wu, Tingwen Huang, Shun-Yan Ren
    Pages 185-209

  12. Back Matter

    Pages 211-220
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Keywords

About this book

This book introduces selected recent findings on the analysis and control of dynamical behaviors for coupled reaction-diffusion neural networks. It presents novel research ideas and essential definitions concerning coupled reaction-diffusion neural networks, such as passivity, adaptive coupling, spatial diffusion coupling, and the relationship between synchronization and output strict passivity. Further, it gathers research results previously published in many flagship journals, presenting them in a unified form. As such, the book will be of interest to all university researchers and graduate students in Engineering and Mathematics who wish to study the dynamical behaviors of coupled reaction-diffusion neural networks.

Authors and Affiliations

  • Tianjin Polytechnic University , Tianjin, China

    Jin-Liang Wang, Shun-Yan Ren

  • Beihang University , Beijing, China

    Huai-Ning Wu

  • Texas A&M University at Qatar , Doha, Qatar

    Tingwen Huang

Bibliographic Information

  • Book Title: Analysis and Control of Coupled Neural Networks with Reaction-Diffusion Terms

  • Authors: Jin-Liang Wang, Huai-Ning Wu, Tingwen Huang, Shun-Yan Ren

  • DOI: https://doi.org/10.1007/978-981-10-4907-1

  • Publisher: Springer Singapore

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer Nature Singapore Pte Ltd. 2018

  • Hardcover ISBN: 978-981-10-4906-4Published: 16 June 2017

  • Softcover ISBN: 978-981-13-5262-1Published: 12 January 2019

  • eBook ISBN: 978-981-10-4907-1Published: 07 June 2017

  • Edition Number: 1

  • Number of Pages: XIII, 220

  • Number of Illustrations: 2 b/w illustrations, 41 illustrations in colour

  • Topics: Control and Systems Theory, Mathematical Models of Cognitive Processes and Neural Networks, Artificial Intelligence, Complex Systems

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