Extended Dissipative Approach for Anti-Synchronization of Delayed Inertial Valued Neural Networks via Event-Hybrid Triggered Control with Deception Attacks

This paper investigates the problems of anti-synchronization for a class of inertial neural networks (INNs) with time-varying delays under the influence of deception attacks and hybrid triggered control. A novel dynamic hybrid-triggered control (DHTC) scheme is developed to utilize communication resources and enhance network security efficiently for the model INNs. By integrating the extended dissipative approach with Lyapunov–Krasovskii functional (LKF) techniques, new sufficient conditions are established to ensure the quadratic stability of the resulting closed-loop system. The proposed framework not only unifies the anti-synchronization problems but also extends classical passivity, (Q, S, R)-dissipative, H∞, and L2−L∞ results as special cases. Moreover, the DHTC mechanism dynamically switches between time-triggered and event-triggered modes, reducing unnecessary signal transmissions while maintaining system stability against deception attacks. Finally, simulation results on delayed INNs demonstrate the effectiveness and superiority of the proposed theoretical and control strategy.