Adaptive Event-Triggered Projective Synchronization for FOCVNNs Subject to Aperiodic DoS Attacks

This article focuses on the projective synchronization control problem for a class offractional-order complex-valued neural networks (FOCVNNs) with additive time-varyingdelays (ATVDs) subject to aperiodic denial-of-service (DoS) attacks. Initially, a switchingdelayFOCVNN model is designed to address the intermittent and unpredictable nature ofaperiodic DoS attacks. Secondly, an adaptive event-triggering mechanism (AETM) with asampled-data-based switching-adjusted threshold parameter is proposed, which can savenetwork bandwidth effectively and strengthen the system’s defense against aperiodic DoSattacks. Third, leveraging event-triggered information, a switching controller for projectivesynchronization is designed to counteract the effects of DoS attacks and maintain systemstability during intermittent data transmission failures. Subsequently, a novel commonLyapunov–Krasovskii function (LKF) is constructed for both the attack and dormant phasesof DoS attacks, and by utilizing the fractional-order inequality method, the sufficient conditionsfor the projective synchronization are presented as linear matrix inequalities (LMIs).Finally, numerical examples confirm the practicality and effectiveness of the theoreticalresults, and demonstrate its capacity to sustain robust synchronization performance incomplex attack scenarios.