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Finite-Time Passivity for Coupled Fractional-Order Neural Networks With Multistate or Multiderivative Couplings
被引:16
作者:
Liu, Chen-Guang
[1
]
Wang, Jin-Liang
[2
,3
]
Wu, Huai-Ning
[4
,5
]
机构:
[1] Tiangong Univ, Sch Comp Sci & Technol, Tianjin 300387, Peoples R China
[2] Tiangong Univ, Sch Comp Sci & Technol, Tianjin Key Lab Autonomous Intelligence Technol &, Tianjin 300387, Peoples R China
[3] Linyi Univ, Sch Informat Sci & Technol, Linyi 276005, Shandong, Peoples R China
[4] Beihang Univ, Sch Automat Sci & Elect Engn, Sci & Technol Aircraft Control Lab, Beijing 100191, Peoples R China
[5] Peng Cheng Lab, Shenzhen 518000, Peoples R China
基金:
中国国家自然科学基金;
关键词:
Couplings;
Synchronization;
Neural networks;
Adaptive systems;
Symmetric matrices;
Stability criteria;
Numerical stability;
Coupled fractional-order neural networks (CFNNs);
finite-time passivity (FTP);
multiderivative couplings;
multistate couplings;
STABILITY ANALYSIS;
STABILIZATION;
D O I:
10.1109/TNNLS.2021.3132069
中图分类号:
TP18 [人工智能理论];
学科分类号:
081104 ;
0812 ;
0835 ;
1405 ;
摘要:
This article mainly delves into the finite-time passivity (FTP) for coupled fractional-order neural networks with multistate couplings (CFNNMSCs) or coupled fractional-order neural networks with multiderivative couplings (CFNNMDCs). Distinguishing from the traditional FTP definitions, several concepts of FTP for fractional-order systems are given. On one hand, we present several sufficient conditions to ensure the FTP for CFNNMSCs by artfully designing a state-feedback controller and an adaptive state-feedback controller. On the other hand, by utilizing some inequality techniques, two sets of FTP criteria for CFNNMDCs are also established on the basis of the state-feedback and adaptive state-feedback controllers. Finally, numerical examples are used to demonstrate the validity of the derived FTP criteria.
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页码:5976 / 5987
页数:12
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