In　order　to　improve　the　overestimation　of　ocular　artifacts　(OA)　in　electroencephalogram　(EEG)　and　the　OA　removal　effect　of　nonlinear　mixture　caused　by　environmental　interference　coupling,　a　novel　automatic　removal　method　is　proposed　based　on　fast　kernel　independent　component　analysis　(FastKICA)　and　discrete　wavelet　transform　(DWT),　and　it　is　denoted　as　FKIWT.　The　independent　components　are　separated　from　the　mixed　EEG　by　using　the　FastKICA　algorithm,　and　the　correlation　coefficient　is　applied　to　identify　OA　component;　Then,　the　Multiresolution　analysis　of　OA　is　achieved　with　DWT,　the　approximation　wavelet　coefficients　are　set　to　zero　and　the　detail　wavelet　coefficients　are　not　changed.　So　more　useful　EEG　is　remained　in　the　reconstructed　OA　component;　Furthermore,　the　clean　EEG　is　restored　with　the　inverse　algorithm　of　FastKICA.　The　experimental　results　show　that　FKIWT　can　effectively　improve　the　overestimation　of　OA　and　has　perfect　anti-interference　ability　and　robustness.　Meanwhile,　the　better　effects　of　OA　elimination　are　also　obtained　on　the　condition　that　the　linear　or　nonlinear　mixed　model　is　adopted,　and　the　latter＇s　advantage　is　especially　obvious.　The　FKIWT　is　suitable　for　on-line　application.　©　2016,　Chinese　Institute　of　Electronics.　All　right　reserved.