Journal
NEUROCOMPUTING
Volume 450, Issue -, Pages 311-318Publisher
ELSEVIER
DOI: 10.1016/j.neucom.2021.04.043
Keywords
Complex-valued neural networks; Fractional-order calculus; Stability; Probabilistic time-varying delays; Linear matrix inequality
Categories
Funding
- National Natural Science Foundation of China [61773004]
- Science and Technology Research Program of Chongqing Education Commission of China [KJZD-M202000701]
- Team Building Project for Graduate Tutors in Chongqing [JDDSTD201802]
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This paper investigates the stability of fractional-order complex-valued neural networks with probabilistic time varying delays and provides a numerical example to verify the feasibility of the theoretical result.
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. (c) 2021 Elsevier B.V. All rights reserved.
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