Fault diagnosis of analog IC based on wavelet neural network ensemble - 文章详情页

作者：

Zuo, Lei (Zuo, Lei.) | Hou, Ligang (Hou, Ligang.) | Wu, Wuchen (Wu, Wuchen.) (学者：吴武臣) | Wang, Jinhui (Wang, Jinhui.) | Geng, Shuqin (Geng, Shuqin.)

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摘要：

A　new　method　of　analog　IC　fault　diagnosis　is　proposed　in　this　paper,　which　is　based　on　wavelet　neural　network　ensemble　(WNNE)　technique　and　Adaboost　algorithm.　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　fault　diagnosis　of　a　radar　scanning　circuit　is　implemented　with　this　new　method.　The　simulation　results　show　that　the　new　method　is　more　effective　than　the　traditional　wavelet　neural　network　(WNN)　method.　©　2009　Springer　Berlin　Heidelberg.

关键词：

Adaptive boosting Analog integrated circuits Failure analysis Fault detection Neural networks Timing circuits Wavelet decomposition

作者机构：

[ 1 ] [Zuo, Lei]VLSI and System Lab, Beijing University of Technology, Beijing 100022, China
[ 2 ] [Hou, Ligang]VLSI and System Lab, Beijing University of Technology, Beijing 100022, China
[ 3 ] [Wu, Wuchen]VLSI and System Lab, Beijing University of Technology, Beijing 100022, China
[ 4 ] [Wang, Jinhui]VLSI and System Lab, Beijing University of Technology, Beijing 100022, China
[ 5 ] [Geng, Shuqin]VLSI and System Lab, Beijing University of Technology, Beijing 100022, China

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