Journal
NEUROCOMPUTING
Volume 275, Issue -, Pages 2080-2092Publisher
ELSEVIER
DOI: 10.1016/j.neucom.2017.10.035
Keywords
Memristor; Passivity Reaction-diffusion term; Poincare inequality; Linear matrix inequality (LMI)
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Funding
- Fundamental Research Funds for the Central Universities [106112015CDJXY100002]
- Scientific and Technological Research Program of Chongqing Municipal Education Commission [KJ1501002]
- National Natural Science Foundation of China [61603125]
- Program of Higher Education of He'nan Province [17A120001]
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In this paper, we put in effort to inspect the passivity and exponential passivity problem of memristive neural networks with time-varying delays and reaction-diffusion term. Based on the basis of generalized Lyapunov approach, Poincare inequality, Schur complement Lemma, free-weighting matrix approach as well as some inequality techniques, the main conclusions of this paper are derived in the form of linear matrix inequality (LMI). What is noteworthy is that the obtained sufficient criteria rely on the reaction-diffusion term, which implies that the reaction-diffusion term can effect the passivity of the given system. Finally, two numerical examples are emerged to check the practicability of the derived passivity conditions. (C) 2017 Elsevier B.V. All rights reserved.
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