Event-Triggered Synchronization of Multiple Discrete-Time Markovian Jump Memristor- Based Neural Networks With Mixed Mode-Dependent Delays

IEEE Transactions on Circuits and Systems I: Regular Papers(2022)

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摘要
This paper deals with global synchronization problem of multiple discrete-time Markovian jump memristor-based neural networks (DTMJMNNs) with mixed mode-dependent delays via a novel event-triggered impulsive coupling control (ETICC). The parameters of the multiple DTMJMNNs and the mixed time delays (both discrete and distributed delays) switch randomly according to a Markov chain. In the ETICC strategy, the controller does not work all the time, but only works at impulse instants determined by specific events. In particular, the coupling matrix can be non-Laplacian. By using the Lyapunov stability theory, linear matrix inequalities (LMIs), and the Kronecker product, some sufficient conditions for global synchronization of multiple DTMJMNNs under the event-triggered strategy are derived. Two examples are presented to test the validity of the theoretical analysis results.
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关键词
Synchronization,memristor-based neural networks,Markovian jump,event-triggered impulsive coupling,mixed time delays
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