Analog Circuits Fault Diagnosis Using Support Vector Machine

Support vector machine (SVM) is a machine learning algorithm based on statistical theory, which has advantages of simple structure and strong generalization ability as well as classification ability to a few samples. A new method of analog circuit fault diagnosis based SVM is presented in this paper. The method of circuit fault signatures selection is introduced and the model of analog circuit fault based SVM is obtained. The simulation results of a biquadratic filter testified that the proposed approach for analog circuit fault diagnosis is superior to conventional ones and is to increase the fault diagnosis accuracy.

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