Journal
NEUROCOMPUTING
Volume 171, Issue -, Pages 524-531Publisher
ELSEVIER
DOI: 10.1016/j.neucom.2015.06.078
Keywords
Inertial neural networks; Time-varying; Global exponential attractive set; Lagrange exponential stability
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Funding
- National Natural Science Foundation of China [61272530, 11072059]
- Natural Science Foundation of Jiangsu Province of China [BK2012741]
- Specialized Research Fund for the Doctoral Program of Higher Education [20110092110017, 20130092110017]
- Natural Science Foundation Project of CQ CSTC [cstc2014jcyjA00022]
- Chongqing Municipal Education Commission [KJ1401003, KJ1501002]
- Chongqing Three Gorges University [14QN22]
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In this paper, the global exponential stability in Lagrange sense related to inertial neural networks with time-varying delay is investigated. Firstly, by constructing a proper variable substitution, the original system is transformed into the first order differential system. Next, some succinct criteria for the ultimate boundedness and global exponential attractive set are derived via the Lyapunov function method, inequality techniques and analytical method. Meanwhile, the detailed estimations for the global exponential attractive set are established. Finally, the effectiveness of theoretical results has been illustrated via two numerical examples. (C) 2015 Elsevier B.V. All rights reserved.
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