Optimization of Testing Stimulus for Nonlinear Circuits by Applying Elman Neural Network

The parameters of transient testing stimulus for nonlinear analog circuits greatly influence the fault diagnosis efficiency. In the course of finding the optimum stimulus, we have to develop the nonlinear analog circuits' models. Elman network which is a dynamic recurrent neural network can approximate any dynamic nonlinear system. In this paper, Elman network is used to develop the models of the fault circuits and fault free circuit, the optimum stimulus is searched with genetic algorithm. Experiment results demonstrate that the optimum stimulus achieved has high fault identification.