This paper proposes a method for analog fault diagnosis using neural networks. The primary focus of the paper is to provide robust diagnosis using a mechanism to deal with the problem of component tolerances and reduce testing time. The proposed approach is based on the k-fault diagnosis method and artificial backward propagation neural network. Simulation results show that the method is robust and fast for fault diagnosis of analog circuits with tolerances.
|Title of host publication||In: Procs of IEEE Asia-Pacific Conference on Circuits and Systems, APCCAS 2000|
|Publisher||Institute of Electrical and Electronics Engineers (IEEE)|
|Publication status||Published - 2000|