In　this　paper,　the　global　asymptotic　stability　of　memristive　bidirectional　associative　memory　neural　networks　with　leakage　delay　and　two　additive　time-varying　delays　is　firstly　studied.　Then,　we　propose　a　novel　sampled-data　feedback　controller　to　guarantee　the　synchronization　of　system　based　on　drive/response　concept.　In　particular,　taking　full　advantage　of　the　input　delay　approach,　the　Lyapunov　function　method　and　the　Jensen＇s　inequality　theory,　several　sufficient　conditions　are　obtained.　Finally,　two　numerical　simulation　examples　show　the　effectiveness　of　the　designed　sampled-data　control　strategy.　Furthermore,　our　results　can　be　applied　to　simulate　the　associative　memory　function　of　brain-like　robots,　large-scale　information　storage,　etc.　(C)　2017　Published　by　Elsevier　Ltd.