Passivity analysis of coupled neural networks with reaction-diffusion terms and mixed delays
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2018 The Franklin Institute In this paper, we intend to discuss the passivity of coupled neural networks (NNs) with reactiondiffusion terms and mixed delays. By constructing appropriate Lyapunov functional, and with the help of liner matrix inequalities, some inequality techniques, several sufficient conditions are derived to guarantee the output strictly passive, input strictly passive, passive of the proposed neural network model. Then, a stability criterion is presented according to the obtained passivity results. Moreover, the proposed neural network model herein is more general than some recent studies, which can improve and enrich the previous research results. Finally, a numerical example is presented to show the effectiveness of the theoretical criteria.