Analog Circuit Fault Diagnosis Based on Rough Set and LVQ

来源 :2014年国际计算机科学与软件工程学术会议 | 被引量 : 0次 | 上传用户:scotscotscotscot
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  In order to solve the difficulty of recognition in analog circuit fault diagnosis,under the two aspects of analog circuit fault feature extraction and fault pattern recognition,combined with their respective characteristics of rough set theory (RS) and the learning vector quantization (LVQ) neural network,a new analog circuit fault diagnosis method based on rough set and learning vector quantization is proposed in this paper.The RS method is used in analog circuit fault feature dimension reduction,classification and the application of LVQ network in fault mode.Simulation results show that,under the same precision request,this algorithm training time is far smaller than the ordinary evolution neural network,and this method has certain practical significance in the fault diagnosis for analog circuits.
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