Event-triggered finite-time synchronization for uncertain neural networks with quantizations

Computational and Applied Mathematics(2022)

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摘要
This paper concentrates on the problem of event-triggered finite-time quantized synchronization for uncertain neural networks. We initially establish a synchronization model for neural networks with input quantization and event-triggered mechanism. Then, the finite-time synchronization criterion for the neural networks is deduced by Lyapunov functional and free-weighting matrix schemes. Utilizing variable separation approach, finite-time synchronization controller and event-triggered matrix parameter are co-designed in terms of the feasibility of linear matrix inequalities. Additionally, the effectiveness of the proposed methods is evaluated by a simulation example.
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关键词
Neural networks, Event-triggered mechanism, Variable separation method, Quantization, Finite-time synchronization, 24D06, 34H05, 93D05, 15A39
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