<p>This paper investigates the finite-time synchronization of complex-valued memristive neural networks (CVMNNs) with time-varying delays using an event-triggered control approach. The analysis is conducted in a holistic manner, utilizing the one-norm and sign functions of complex numbers, thereby eliminating the need for decomposition. To alleviate communication pressure, an event-triggered controller is introduced, accompanied by specific conditions and criteria to guarantee synchronization within a finite time frame. Additionally, a direct estimate of the synchronization time is provided, and a positive lower bound on the minimum event interval is derived to prevent Zeno behavior. Building on this event-triggered strategy, a self-triggered mechanism is designed to eliminate the necessity for continuous monitoring. The proposed method is straightforward and easily implementable, with its effectiveness demonstrated through illustrative examples and simulation results.</p>