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Adaptive Event-Triggered Projective Synchronization for FOCVNNs Subject to Aperiodic DoS Attacks
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DOI：10.3390/fractalfract10080534.png)
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Abstract
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This article focuses on the projective synchronization control problem for a class of fractional-order complex-valued neural networks (FOCVNNs) with additive time-varying delays (ATVDs) subject to aperiodic denial-of-service (DoS) attacks. Initially, a switchingdelay FOCVNN model is designed to address the intermittent and unpredictable nature of aperiodic DoS attacks. Secondly, an adaptive event-triggering mechanism (AETM) with a sampled-data-based switching-adjusted threshold parameter is proposed, which can save network bandwidth effectively and strengthen the system’s defense against aperiodic DoS attacks. Third, leveraging event-triggered information, a switching controller for projective synchronization is designed to counteract the effects of DoS attacks and maintain system stability during intermittent data transmission failures. Subsequently, a novel common Lyapunov–Krasovskii function (LKF) is constructed for both the attack and dormant phases of DoS attacks, and by utilizing the fractional-order inequality method, the sufficient conditions for the projective synchronization are presented as linear matrix inequalities (LMIs). Finally, numerical examples confirm the practicality and effectiveness of the theoretical results, and demonstrate its capacity to sustain robust synchronization performance in complex attack scenarios.
Keywords:
adaptive event-triggered mechanism
fractional-order complex-valued neural networks
aperiodic denial of service attacks
projective synchronization
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