Passivity analysis of delayed reaction-diffusion memristor-based neural networks.

Publication Type:
Journal Article
Neural Netw, 2019, 109, pp. 159-167
Issue Date:
Filename Description Size
1-s2.0-S0893608018302892-main.pdfPublished version1.47 MB
Adobe PDF
Full metadata record
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.
Please use this identifier to cite or link to this item: