Analysis and Control of Coupled Neural Networks with Reaction-Diffusion Terms
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 networ
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is and Control of Coupled Neural Networks with ReactionDiffusion Terms
Analysis and Control of Coupled Neural Networks with Reaction-Diffusion Terms
Jin-Liang Wang Huai-Ning Wu Tingwen Huang Shun-Yan Ren •
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Analysis and Control of Coupled Neural Networks with Reaction-Diffusion Terms
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Jin-Liang Wang Tianjin Polytechnic University Tianjin China
Tingwen Huang Texas A&M University at Qatar Doha Qatar
Huai-Ning Wu Beihang University Beijing China
Shun-Yan Ren Tianjin Polytechnic University Tianjin China
ISBN 978-981-10-4906-4 DOI 10.1007/978-981-10-4907-1
ISBN 978-981-10-4907-1
(eBook)
Library of Congress Control Number: 2017940609 © Springer Nature Singapore Pte Ltd. 2018 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Printed on acid-free paper This Springer imprint is published by Springer Nature The registered company is Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore
Preface
Up to date, many researchers have devoted much effort to dynamical behaviors for coupled neural networks (CNNs) because of their wide applications in different fields. For instance, the CNNs have been triumphantly applied to harmonic oscillation generation, chaos generators design, secure communication, the electronic circuits, and memorizing and reproducing complex oscillatory patterns. Moreover, the research about synchronization of CNNs is a significant step to comprehend brain science. On the other hand, it is well known that neural networks are implemented by electric circuits, and the diffusion phenomena inevitably appear in electric circuits once electrons transport in a nonuniform electromagnetic field. Obviously, it is extremely necessary to consider the diffusion phenomena in coupled neural networks. Therefore, the investigation of dynamical behaviors about coupled reaction-di
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