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Robust Fault Diagnosis of Analog Circuits with Tolerances
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作者 ying deng1, yigang he1 , xu he2 ,yichuang sun3 1. college of electrical and information engineering,hunan university, 410082, changsha, hunan, china 2. department of computer science, hunan university, 410082, changsha, hunan, china 3. department of ele 《湖南大学学报(自然科学版)》 EI CAS CSCD 2000年第S2期133-138,共6页
A method for robust analog fault diagnosis using hybrid neural networks is proposed. The primary focus of the paper is to provide robust diagnosis using a mechanism to deal with the problem of element tolerances and r... A method for robust analog fault diagnosis using hybrid neural networks is proposed. The primary focus of the paper is to provide robust diagnosis using a mechanism to deal with the problem of element tolerances and reduce testing time. The proposed approach is based on the fault dictionary diagnosis method and backward propagation neural network (BPNN) and the adaptive resonance theory (ART) neural network. Simulation results show that the method is robust and fast for fault diagnosis of analog circuits with tolerances. 展开更多
关键词 ANALOG CIRCUITS FAULT diagnosis TOLERANCES Artificial NEURAL networ|
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