期刊
NEURAL NETWORKS
卷 98, 期 -, 页码 203-211出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.neunet.2017.11.017
关键词
Cohen-Grossberg neural networks; Impulses; Fixed-time stability; Stabilization; BAM neural networks
资金
- National Natural Science Foundation of People's Republic of China [61633011, 61374078]
- Chongqing Research Program of Basic Research and Frontier Technology [cstc2015jcyjBX0052]
- Graduate Student Research Innovation Project of Chongqing [CYB17076]
- Qatar National Research Fund (Qatar Foundation) [NPRP 4-1162-1-181]
This article is concerned with the fixed-time stabilization for impulsive Cohen-Grossberg BAM neural networks via two different controllers. By using a novel constructive approach based on some comparison techniques for differential inequalities, an improvement theorem of fixed-time stability for impulsive dynamical systems is established. In addition, based on the fixed-time stability theorem of impulsive dynamical systems, two different control protocols are designed to ensure the fixed-time stabilization of impulsive Cohen-Grossberg BAM neural networks, which include and extend the earlier works. Finally, two simulations examples are provided to illustrate the validity of the proposed theoretical results. (C) 2017 Elsevier Ltd. All rights reserved.
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