期刊
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
卷 33, 期 11, 页码 6473-6483出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNNLS.2021.3080830
关键词
Biological neural networks; Stability criteria; Numerical stability; Mathematical model; Neurons; Lyapunov methods; Learning systems; Delayed coupled neural networks; existence of solutions; feedback control; fractional-order; Mittag-Leffler stability; reaction-diffusion
类别
资金
- National Natural Science Foundation of China [61873071]
- Shandong Provincial Natural Science foundation [ZR2019MF006, ZR2020ZD27]
- National Research Foundation of Korea (NRF) Grant funded through the Korea Government (MSIT) [2020R1A2B5B02002002]
This article mainly considers the existence of solutions and global Mittag-Leffler stability of delayed fractional-order coupled reaction-diffusion neural networks without strong connectedness. Criteria for the existence of solutions and global Mittag-Leffler stability are provided using Leary-Schauder's fixed point theorem and the Lyapunov method. The correctness of the theory is verified through a numerical example.
In this article, we mainly consider the existence of solutions and global Mittag-Leffler stability of delayed fractional-order coupled reaction-diffusion neural networks without strong connectedness. Using the Leary-Schauder's fixed point theorem and the Lyapunov method, some criteria for the existence of solutions and global Mittag-Leffler stability are given. Finally, the correctness of the theory is verified by a numerical example.
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