Event-triggered finite-time synchronization of fractional-order quaternion-valued neural networks with generalized piecewise constant argument

Abstract

This article investigates the finite-time synchronization (FTS) of fractional-order quaternion-valued neural networks (FQNNs) with a generalized piecewise constant argument (GPCA). First, the relationship between the current value and the deviation variable is established. To relieve the communication pressure, a proper event-triggered controller is designed, then the event-triggered conditions and some criteria are also established to guarantee the FTS. Moreover, the positive lower bound of the inter-event time is obtained to get rid of the Zeno behavior. The results of this study advance the synchronization theory of fractional-order systems, extending existing findings from integer-order systems to fractional-order systems. Finally, the obtained theoretical result is validated through numerical simulation.