A New Method for Event‐Triggered Synchronization of Fractional‐Order Delayed BAM Neural Networks in Finite Time
Shangbin Xu, Hai Zhang, Renyu Ye, Xiang Hong Wu, Jinde Cao · Mathematical Methods in the Applied Sciences · 2025
ABSTRACT This article aims to study the finite‐time synchronization (FTS) problem of a class of bidirectional associative memory neural networks (BAMNNs) with time delays. Initially, leveraging properties of fractional calculus and common inequality techniques, a novel fractional FTS lemma is rigorously derived, which extends many existing FTS lemmas. Subsequently, an event‐triggered control (ETC) mechanism is devised, and with the aid of the newly established FTS lemma, sufficient conditions for achieving FTS in BAMNNs are formulated. Ultimately, the accuracy of the derived results is verified by a computational illustration.