Finite-Time Synchronization of Fractional-Order Fuzzy Time-Varying Coupled Neural Networks Subject to Reaction-Diffusion

被引:21
作者
Xu, Yao [1 ]
Liu, Wenxi [2 ]
Wu, Yongbao [3 ]
Li, Wenxue [1 ]
机构
[1] Harbin Inst Technol, Dept Math, Weihai 264209, Peoples R China
[2] Harbin Inst Technol, Dept Automat, Weihai 264209, Peoples R China
[3] Southeast Univ, Sch Automat, Nanjing 210096, Peoples R China
基金
中国国家自然科学基金;
关键词
Artificial neural networks; Synchronization; Lyapunov methods; Couplings; Neurons; Feedback control; Mathematical models; Finite-time synchronization; fractional-order networks; fuzzy time-varying coupled neural networks; reaction-diffusion; UNIFORM STABILITY;
D O I
10.1109/TFUZZ.2023.3257100
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this article, finite-time synchronization is investigated for fractional-order fuzzy time-varying coupled neural networks subject to reaction-diffusion by establishing a new framework under fuzzy-based feedback control and fuzzy-based adaptive control. For the considered networks, we put forward an innovative graph-theory-based time-varying Lyapunov function. To overcome the difficulty of estimating the fractional derivative of this function, this article proposes a novel fractional derivative rule. Through graph theory and the Lyapunov method, several finite-time synchronous criteria are obtained for the considered networks, and the estimation of the settling time is derived. Finally, the numerical results are shown to demonstrate the practicability of the given results.
引用
收藏
页码:3423 / 3432
页数:10
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