Analog Circuit Fault Diagnosis Based on Local Graph Embedding Weighted-Penalty SVM
Liao Jian1, 2, Shi Xianjun2, Zhou Shaolei2, Xiao Zhicai2
1. The Troop 91550 of PLA Dalian 116000 China; 2. Department of Control Engineering Naval Aeronautical and Astronautical University Yantai 264001 China
Abstract This paper proposes a method for analog IC diagnosis based on local graph embedding weighted-penalty support vector machine (SVM), to overcome the shortcomings of fault diagnosis method based on traditional SVM. A new type of SVM lying on data distribution is designed. Herein, maximize the inter-class margin of the entire data while optimizing local distribution of the data manifold, meanwhile, introduce the global data distribution information in error costs. The proposed method effectively combines the prior distribution information to improve the robustness and increase the diagnosis accuracy. The simulation results show the effectiveness of the algorithm.
Liao Jian,Shi Xianjun,Zhou Shaolei等. Analog Circuit Fault Diagnosis Based on Local Graph Embedding Weighted-Penalty SVM[J]. Transactions of China Electrotechnical Society, 2016, 31(4): 28-35.
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2016, Vol. 31 
