A　fault　diagnosis　method　for　analog　IC　diagnosis　based　on　wavelet　neural　network　ensemble　(WNNE)　and　Adaboost　algorithm,　is　proposed　in　this　paper.　This　makes　the　way　of　the　directory　be　of　use　in　fault,　and　enhances　the　validity　of　the　fault　diagnosis.　Using　wavelet　decomposition　as　a　tool　for　extracting　feature,　Then,　after　training　the　WNNE　by　faulty　feature　vectors,　the　model　of　the　circuit　with　fault　diagnosis　system　is　built.　Simulation　results　have　shown　that　this　claim　is　more　effective　than　wavelet　neural　network　(WNN).