期刊
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
卷 33, 期 9, 页码 4515-4526出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNNLS.2021.3057861
关键词
Stability criteria; Neural networks; Numerical stability; Circuit stability; Delays; Uncertainty; Learning systems; Fractional-order competitive neural networks (FOCNNs); multistability; stabilization; unbounded time-varying delays
类别
资金
- Natural Science Foundation of China [61906071, 61936004, 61673188]
- China Postdoctoral Science Foundation [2019M652645]
- Innovation Group Project of the National Natural Science Foundation of China [61821003]
- Foundation for Innovative Research Groups of Hubei Province of China [2017CFA005]
- 111 Project on Computational Intelligence and Intelligent Control [B18024]
This article investigates the multistability and stabilization of fractional-order competitive neural networks with unbounded time-varying delays, deriving conditions for coexistence of equilibrium points and multiple mu-stability through analytical methods. The results enrich and improve previous findings in the field, and are demonstrated to be effective through numerical examples.
This article investigates the multistability and stabilization of fractional-order competitive neural networks (FOCNNs) with unbounded time-varying delays. By utilizing the monotone operator, several sufficient conditions of the coexistence of equilibrium points (EPs) are obtained for FOCNNs with concave-convex activation functions. And then, the multiple mu-stability of delayed FOCNNs is derived by the analytical method. Meanwhile, several comparisons with existing work are shown, which implies that the derived results cover the inverse-power stability and Mittag-Leffler stability as special cases. Moreover, the criteria on the stabilization of FOCNNs with uncertainty are established by designing a controller. Compared with the results of fractional-order neural networks, the obtained results in this article enrich and improve the previous results. Finally, three numerical examples are provided to show the effectiveness of the presented results.
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