期刊
NEURAL NETWORKS
卷 95, 期 -, 页码 102-109出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.neunet.2017.03.012
关键词
Delayed impulsive; Exponential stability; Impulsive; Inertial memristor-based neural network; Time delay
资金
- Fundamental Research Funds for the Central Universities [XDJK2016BC137, SWU116004]
- Natural Science Foundation of China [61633011, 61703346, 61773320]
- NPRP from the Qatar National Research Fund (Qatar Foundation) [NPRP 9 166-1-031]
In this study, we investigate the global exponential stability of inertial memristor-based neural networks with impulses and time-varying delays. We construct inertial memristor-based neural networks based on the characteristics of the inertial neural networks and memristor. Impulses with and without delays are considered when modeling the inertial neural networks simultaneously, which are of great practical significance in the current study. Some sufficient conditions are derived under the framework of the Lyapunov stability method, as well as an extended Halanay differential inequality and a new delay impulsive differential inequality, which depend on impulses with and without delays, in order to guarantee the global exponential stability of the inertial memristor-based neural networks. Finally, two numerical examples are provided to illustrate the efficiency of the proposed methods. (C) 2017 Elsevier Ltd. All rights reserved.
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