Synchronization of reaction‐diffusion neural networks with distributed delay via quantized boundary control
Summary This paper investigates the synchronization of reaction‐diffusion neural networks (RDNNs) with distributed delay via quantized boundary control. To reduce the communication burden, a novel control strategy combined boundary control and logarithmic quantizer is proposed, and two controllers r...
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Published in | International journal of adaptive control and signal processing Vol. 37; no. 5; pp. 1166 - 1177 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
Bognor Regis
Wiley Subscription Services, Inc
01.05.2023
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Subjects | |
Online Access | Get full text |
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Summary: | Summary
This paper investigates the synchronization of reaction‐diffusion neural networks (RDNNs) with distributed delay via quantized boundary control. To reduce the communication burden, a novel control strategy combined boundary control and logarithmic quantizer is proposed, and two controllers respectively subject to constant and adaptive coefficients are carried out. Worth mentioning that the adaptive feedback gain is a matrix in this paper rather than a one‐dimensional variable in most of the existing literatures. Using the Lyapunov functional, the sufficient conditions for delay‐dependent synchronization are obtained through linear matrix inequalities. The effectiveness of the proposed control strategy is illustrated via two examples. |
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Bibliography: | Funding information China Postdoctoral Science Foundation, Grant/Award Number: 2020M672024; Youth Creative Team Sci‐Tech Program of Shandong Universities, Grant/Award Number: 2019KJI007; National Natural Science Foundation of China, Grant/Award Numbers: 62003189; 61973189; 61702356; Natural Science Foundation of Shandong Province, Grant/Award Number: ZR2021MA043 ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
ISSN: | 0890-6327 1099-1115 |
DOI: | 10.1002/acs.3567 |