Global asymptotic stability of fractional-order complex-valued neural networks with probabilistic time-varying delays

Sihan Chen,Qiankun Song,Zhenjiang Zhao,Yurong Liu,Fuad E Alsaadi

doi:10.1016/j.neucom.2021.04.043

Global asymptotic stability of fractional-order complex-valued neural networks with probabilistic time-varying delays

Sihan Chen, Qiankun Song + Show 3 more

https://doi.org/10.1016/j.neucom.2021.04.043

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Journal: Neurocomputing	Publication Date: Apr 17, 2021
Citations: 26

Affiliation: Chongqing Jiaotong University, Huzhou University, Yancheng Institute of Technology, Yangzhou University, King Abdulaziz University

#Probabilistic Time-varying Delays #Fractional-order Complex-valued Neural Networks + Show 8 more

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Abstract

The stability of fractional-order complex-valued neural networks (FOCVNNs) with probabilistic time-varying delays is investigated in this paper. By constructing suitable Lyapunov–Krasovskii functional and utilizing inequality technique, a complex-valued linear matrix inequality (LMI) criterion guaranteeing the global asymptotic stability of the proposed FOCVNNs is deduced. A numerical example with simulations is provided to demonstrate the feasibility and availability of the obtained theoretical result.

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