Synchronization of Coupled Memristive Neural Network Based on Edge-Event Triggered Control

This research aims to investigate synchronization issues in coupled memristive neural networks (CMNNs) using both the static and dynamic edge-event triggered control protocols. An interval parameter system is developed by integrating the concept of Filippov solution with differential inclusion theory. Unlike existing work, the suggested edge-event triggered mechanisms don't require the constant information transfer among neighboring nodes, providing a more distributed control approach that reduces system resources since each node communicates asynchronously. Additionally the absence of Zeno behavior at any given moment supports the efficacy of the approach. To demonstrate its viability, a practical simulation example is presented.