期刊
APPLIED MATHEMATICS AND COMPUTATION
卷 338, 期 -, 页码 346-362出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.amc.2018.06.041
关键词
Fractional-order; Complex-valued; Memristive neural networks; Global Mittag-Leffler stability
资金
- Fundamental Research Funds for the Central Universities [2018XKQYMS15]
This paper presents the theoretical results about global Mittag-Leffler stabilization for a class of fractional-order complex-valued memristive neural networks with the designed two types of control rules. As the extension of fractional-order real-valued memristive neural networks, fractional-order complex-valued memristive neural networks have complex-valued states, synaptic weights, and the activation functions. By utilizing the set-valued maps, a generalized fractional derivative inequality as well as fractional-order differential inclusions, several stabilization criteria for global Mittag-Leffler stabilization of fractional-order complex-valued memristive neural networks are established. A numerical example is provided here to illustrate our theoretical results. (C) 2018 Elsevier Inc. All rights reserved.
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