Stability　and　Hopf　bifurcation　of　a　class　of　delayed　complex-valued　neural　networks　are　investigated　in　this　paper.　First,　using　proper　translations　and　coordinate　transformations,　we　decompose　the　activation　functions　and　connection　weights　into　their　real　and　imaginary　parts,　so　as　to　construct　an　equivalent　real-valued　system.　Then,　the　sufficient　conditions　for　Hopf　bifurcation　and　its　directions　are　provided　through　normal　form　theory　and　central　manifold　theorem.　In　the　end,　some　numerical　simulations　are　given　to　illustrate　the　correctness　of　the　results.　(C)　2018　Elsevier　Ltd.　All　rights　reserved.