期刊
NEURAL NETWORKS
卷 109, 期 -, 页码 159-167出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.neunet.2018.10.004
关键词
Neural network; Memristor; Passivity
资金
- Natural Science Foundation of China [61673187, 61673188]
- Qatar National Research Fund (a member of Qatar Foundation) [NPRP 8-274-2-107]
This paper discusses the passivity of delayed reaction- diffusion memristor- based neural networks (RDMNNs). By exploiting inequality techniques and by constructing appropriate Lyapunov functional, several sufficient conditions are obtained in the form of linear matrix inequalities (LMIs), which can be used to ascertain the passivity, output and input strict passivity of delayed RDMNNs. In addition, the passivity of RDMNNs without any delay is also considered. These conditions, represented by LMIs, can be easily verified by virtue of the Matlab toolbox. Finally, some illustrative examples are provided to substantiate the effectiveness and validity of the theoretical results, and to present an application of RDMNN in pseudo- random number generation. (C) 2018 Elsevier Ltd. All rights reserved.
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