A new predefined-time stability theorem and its application in the synchronization of memristive complex-valued BAM neural networks-Reference-Cited by-同舟云学术

A new predefined-time stability theorem and its application in the synchronization of memristive complex-valued BAM neural networks

Published:2022-09 Issue: Volume:153 Page:152-163
ISSN:0893-6080
Container-title:Neural Networks
language:en
Short-container-title:Neural Networks

Author:

Liu Aidi,Zhao Hui^ORCID,Wang Qingjie,Niu Sijie,Gao Xizhan,Chen Chuan,Li Lixiang

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Natural Science Foundation of Beijing Municipality

Natural Science Foundation of Shandong Province

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience

Reference37 articles.

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3. Exponential stability and periodic oscillatory solution in BAM networks with delays;Cai;IEEE Transactions on Neural Networks,2002

4. Global saymptotic stability and adaptive ultimate Mittag-Leffler synchronization for a fractional-order complex-valued memristive neural networks with delays;Chen;IEEE Transactions on Systems Man & Cybernetics:Systems,2018

5. A new fixed-time stability theorem and its application to the fixed-time synchronization of neural networks;Chen;Neural Networks,2020

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