期刊
NEUROCOMPUTING
卷 410, 期 -, 页码 295-303出版社
ELSEVIER
DOI: 10.1016/j.neucom.2020.05.045
关键词
Delayed neural networks; Lyapunov-Krasovskii functional; Auxiliary function-based multiple integral inequality; Stability analysis
资金
- National Natural Science Foundation of China [61973070, 61433004, 61627809]
- Liaoning Revitalization Talents Program [XLYC1802010]
- SAPI Fundamental Research Funds [2018ZCX22]
This paper studies the stability problem for neural networks with time-varying delay. A novel Lyapunov-Krasovskii functional (LKF) is constructed that contains a delay-product-type (DPT) functional and a multiple-integral-type (MIT) functional. Therein, the DPT functional covers some existing ones as its special cases. In order to estimate the derivative of the MIT functional, an auxiliary function-based multiple integral inequality (AFMII) is presented, which can treat some existing results as its special cases. Based on these ingredients, a novel stability condition is obtained for neural networks with time-varying delay. A numerical example is given to illustrate the advantages of the stability condition. (C) 2020 Elsevier B.V. All rights reserved.
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