Novel order-dependent and time-dependent finite-time passivity results on fractional reaction–diffusion memristive neural networks

This work focuses on the finite-time passivity (FTP) of fractional reaction–diffusion memristive neural networks (FRMNNs) with proportional delay via event-triggered control (ETC). To enhance the precision of memristors, uncertain parameters are introduced to FRMNNs, replacing the traditional maximum absolute value method. Based on the established lemma, Schur complement theory and the designed ETC, FTP criteria are derived. Established LMI conditions depend on proportional factor and order, which can demonstrate the input–output energy and finite-time stability (FTS) of the system are influenced by proportional factor and order. Moreover, the event interval has a positive lower bound to prevent the Zeno behavior. Finally, the accuracy of theoretical findings is confirmed via numerical examples.