On the application of artificial neural networks to fault diagnosis in analog circuits with tolerances

This paper proposes a method for analog fault diagnosis by adopting 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 to reduce the testing time. The proposed approach is based on the k-fault diagnosis method and artificial backward propagation neural network, which is shown to be capable of robust diagnosis of analog circuits with tolerances.