Fault Diagnosis of Circuits with Tolerance Based on Support Vector Machines

摘要：

There are many difficulties in diagnosis of analog circuits with tolerance because of the uncertainty characteristic the circuits, it is proposed to construct fault classifiers using the support vector machines (SVMs) algorithm. The fault classifiers based on SVMs can realize precise fault diagnosis even when a few samples are gotten, they have better generality and practicality too. Experiment shows the diagnosis method based on SVMs technique for analog circuits with tolerance types can completely overcome the limitations from some conventional classification methods such as neural networks, achieve nonlinear partition and solve the essential recognition problem for analog circuits with tolerance fault types.

作者: Wang Anna Liu Bumin Qiu Zeng Li Hua

作者单位: School of Information Science & Engineering Northeastern University Shenyang China The College of Micro-Electronics & Solid-state Electronics University of Electronic Science & Techno

会议类型: 国际会议

会议名称: 2006 International Conference on Communications,Circuits and Systems(第四届国际通信、电路与系统学术会议)

会议地点: 广西桂林

会议语种:英文

页码: 2235-2238

在线出版日期: 2006-06-25（万方平台首次上网日期，不代表论文的发表时间）