Abstract
This paper researches the finite-time master–slave synchronization for implicit hybrid neural networks under event-triggered guaranteed cost control and random deception attacks. By developing Lyapunov–Krasovskii functional and exploiting singular value decomposition technique, the finite-time boundedness of synchronization error closed-loop system is achieved under deception attacks and event-triggered scheme, then the finite-time master–slave synchronization of implicit Markovian jump neural networks is realized. The desired gains of state feedback synchronization guaranteed cost controller are designed by solving a set of linear matrix inequalities. The availability of the given approach is confirmed by an artificial neural network and a numerical example.
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