In　this　paper,　a　method　of　ECoG　identification　based　on　SVM　Ensemble　was　proposed　to　solve　the　problems　of　low　classification　accuracy　and　weak　robustness　for　ECoG　collection　during　different　period　of　time.　Common　Spatial　Pattern　(CSP)　algorithm　is　used　for　feature　extraction,　and　Support　Vector　Machine　(SVM)　Ensemble　is　applied　for　classification　of　ECoG.　Besides,　Bagging　algorithm　and　Cross-Validation　technique　are　adopted　in　individual　generation　of　the　SVM　Ensemble.　The　experiment　results　verified　that　the　accuracy　of　SVM　Ensemble　is　better　than　that　of　single　SVM　for　ECoG　collection　in　different　period　of　time,　and　the　Cross-Validated　technique　has　good　performance　than　that　of　Bagging.　Therefore,　SVM　Ensemble　has　stronger　robustness　and　generalization　ability　compared　with　individual　SVMs,　and　will　improve　classification　of　ECoG　signals.