Application of PSO-adaptive neural-fuzzy inference system (ANFIS) in analog circuit fault diagnosis - 文章详情页

作者：

Zuo, Lei (Zuo, Lei.) | Hou, Ligang (Hou, Ligang.) | Zhang, Wang (Zhang, Wang.) | Geng, Shuqin (Geng, Shuqin.) | Wu, Wucheng (Wu, Wucheng.)

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EI Scopus

摘要：

In　order　to　solve　the　problem　of　fault　diagnosis　method　for　analog　IC　diagnosis,　the　method　based　on　Adaptive　Neural-fuzzy　Inference　System　(ANFIS)　is　proposed.　Using　subtractive　clustering　and　Particle　Swarm　Optimization　(PSO)-hybrid　algorithm　as　a　tool　for　building　the　fault　diagnosis　model,　then,　the　model　of　fault　diagnosis　system　was　used　to　the　circuit　fault　diagnosis.　Simulation　results　have　shown　that　the　method　is　more　effective.　©　2010　Springer-Verlag.

关键词：

Analog circuits Analog integrated circuits Failure analysis Fault detection Fuzzy inference Fuzzy logic Fuzzy systems Particle swarm optimization (PSO) Swarm intelligence Timing circuits

作者机构：

[ 1 ] [Zuo, Lei]VLSI and System Lab., Beijing University of Technology, Beijing 100124, China
[ 2 ] [Hou, Ligang]VLSI and System Lab., Beijing University of Technology, Beijing 100124, China
[ 3 ] [Zhang, Wang]VLSI and System Lab., Beijing University of Technology, Beijing 100124, China
[ 4 ] [Geng, Shuqin]VLSI and System Lab., Beijing University of Technology, Beijing 100124, China
[ 5 ] [Wu, Wucheng]VLSI and System Lab., Beijing University of Technology, Beijing 100124, China

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zuolei2000@sina.com

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