Exponential stabilization and synchronization for fuzzy model of memristive neural networks by periodically intermittent control. (English) Zbl 1415.93220
Summary: The problem of exponential stabilization and synchronization for fuzzy model of memristive neural networks (MNNs) is investigated by using periodically intermittent control in this paper. Based on the knowledge of memristor and recurrent neural network, the model of MNNs is formulated. Some novel and useful stabilization criteria and synchronization conditions are then derived by using the Lyapunov functional and differential inequality techniques. It is worth noting that the methods used in this paper are also applied to fuzzy model for complex networks and general neural networks. Numerical simulations are also provided to verify the effectiveness of theoretical results.
MSC:
| 93D20 | Asymptotic stability in control theory |
| 93C42 | Fuzzy control/observation systems |
| 68T05 | Learning and adaptive systems in artificial intelligence |
Keywords:
exponential stabilization; synchronization; fuzzy model of memristive neural networks (MNNs); intermittent controlReferences:
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