Quantized Event-Triggered Synchronization of Discrete-Time Chaotic Neural Networks With Stochastic Deception Attack

This article focuses on the event-triggered synchronization of delayed discrete-time chaotic neural networks with quantized effect and stochastic deception attack. First, for alleviating the network communication and communication burden, an event-triggered mechanism and a logarithmic quantizer are employed, separately. Second, for integrating the impact of event-triggered scheme, quantization, and cyberattack in a unified framework, a synchronization error model is introduced. Third, based on the Lyapunov-Krasvovskii functional (LKF), some sufficient conditions are established to guarantee the synchronization of drive system and response system. Furthermore, the co-design controller and homologous event-triggered parameters are also derived according to the presented asymptotic stability condition. Finally, the availability of the proposed method is verified by some numerical examples.

Automated summary

This article focuses on the event-triggered synchronization of delayed discrete-time chaotic neural networks with quantized effect and stochastic deception attack. An event-triggered mechanism and a logarithmic quantizer are employed to alleviate network communication and burden. A synchronization error model is introduced to integrate the impact of event-triggered scheme, quantization, and cyberattack. The proposed method is verified by numerical examples.