Journal
FUZZY SETS AND SYSTEMS
Volume 443, Issue -, Pages 70-89Publisher
ELSEVIER
DOI: 10.1016/j.fss.2021.10.015
Keywords
Quaternion-valued; Memristor neural networks; Dissipativity; Synchronization; Fuzzy method
Funding
- National Natural Science Foundation of China [61803247]
- Natural Science Foundation of Shaanxi Province [2020JQ-421]
- Fundamental Research Funds for the Central Universities [GK202103005]
- Shaanxi Postdoctoral Science Foundationunder [2018BSHEDZZ129]
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This article presents a dissipativity and synchronization control method for a class of delayed quaternion-valued memristor-based recurrent neural networks. By utilizing Lyapunov functionals, analytical techniques, and novel control algorithms, sufficient conditions are established to achieve dissipativity and synchronization of fuzzy quaternion-valued memristive systems. Additionally, the lexicographical order method is introduced to determine the magnitude of different vectors, and simulation results are provided to demonstrate the effectiveness of the proposed method.
This article focuses on a dissipativity and synchronization control method for a class of delayed quaternion-valued memristor-based recurrent neural networks. On the basis of Lyapunov functionals, analytical techniques, and novel control algorithms, sufficient conditions are established to achieve dissipativity and synchronization of fuzzy quaternion-valued memristive systems. Moreover, the lexicographical order method is introduced, and can be used to determine the magnitude of two different vectors. Finally, corresponding simulation results are provided to show the effectiveness of the proposed method. (C) 2021 Elsevier B.V. All rights reserved.
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