Global attracting set and asymptotic behavior for a class of impulsive functional Hopfield neural networks by a novel vector inequality-Reference-Cited by-同舟云学术

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Global attracting set and asymptotic behavior for a class of impulsive functional Hopfield neural networks by a novel vector inequality

Published:2023-05-20 Issue: Volume: Page:
ISSN:
Container-title:2023 35th Chinese Control and Decision Conference (CCDC)
language:
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Author:

Zhou Weisong¹,Li Guihua¹,Zhu Wei¹

Affiliation:

1. Chongqing University of Posts and Telecommunications,Key Laboratory of Intelligent Analysis and Decision on Complex Systems,Chongqing,P. R. China,400065

Funder

National Natural Science Foundation of China

Chongqing Municipal Education Commission

Chongqing Normal University

Chongqing University of Posts and Telecommunications

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10326447/10326467/10326834.pdf?arnumber=10326834

Reference34 articles.

1. Input-to-state stability of delayed reaction-diffusion neural networks with impulsive effects

2. A Lyapunov Krasovakii Functional for Input-to-State Stability of Infinite-Delayed Systems;xu;proceedings of the 40th Chinese Control Conference,2021

3. Existence and global exponential stability of periodic solution for impulsive Cohen–Grossberg-type BAM neural networks with continuously distributed delays

4. Mean-square exponential input-to-state stability of stochastic delayed neural networks

5. Input-to-state stability of impulsive reaction–diffusion neural networks with infinite distributed delays

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